remove two table tennis and Ball in cup envs

This commit is contained in:
Fabian 2022-07-06 09:10:31 +02:00
parent 6704c9d63a
commit 3a989e179b
74 changed files with 0 additions and 3059 deletions

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@ -1,23 +0,0 @@
from typing import Union, Tuple
import numpy as np
from alr_envs.black_box.raw_interface_wrapper import RawInterfaceWrapper
class MPWrapper(RawInterfaceWrapper):
@property
def context_mask(self):
return np.hstack([
[False] * 111, # ant has 111 dimensional observation space !!
[True] # goal height
])
@property
def current_pos(self) -> Union[float, int, np.ndarray]:
return self.env.sim.data.qpos[7:15].copy()
@property
def current_vel(self) -> Union[float, int, np.ndarray, Tuple]:
return self.env.sim.data.qvel[6:14].copy()

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@ -1,21 +0,0 @@
class AlrReward:
"""
A base class for non-Markovian reward functions which may need trajectory information to calculate an episodic
reward. Call the methods in reset() and step() of the environment.
"""
# methods to override:
# ----------------------------
def reset(self, *args, **kwargs):
"""
Reset the reward function, empty state buffers before an episode, set contexts that influence reward, etc.
"""
raise NotImplementedError
def compute_reward(self, *args, **kwargs):
"""
Returns: Useful things to return are reward values, success flags or crash flags
"""
raise NotImplementedError

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@ -1,361 +0,0 @@
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<compiler angle="radian" meshdir="../../meshes/wam/" />
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</default>
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</default>
</default>
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<mesh name="base_link_convex" file="base_link_convex.stl" />
<mesh name="shoulder_link_fine" file="shoulder_link_fine.stl" />
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<mesh name="shoulder_link_convex_decomposition_p2" file="shoulder_link_convex_decomposition_p2.stl" />
<mesh name="shoulder_link_convex_decomposition_p3" file="shoulder_link_convex_decomposition_p3.stl" />
<mesh name="shoulder_pitch_link_fine" file="shoulder_pitch_link_fine.stl" />
<mesh name="shoulder_pitch_link_convex" file="shoulder_pitch_link_convex.stl" />
<mesh name="upper_arm_link_fine" file="upper_arm_link_fine.stl" />
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<mesh name="upper_arm_link_convex_decomposition_p2" file="upper_arm_link_convex_decomposition_p2.stl" />
<mesh name="elbow_link_fine" file="elbow_link_fine.stl" />
<mesh name="elbow_link_convex" file="elbow_link_convex.stl" />
<mesh name="forearm_link_fine" file="forearm_link_fine.stl" />
<mesh name="forearm_link_convex_decomposition_p1" file="forearm_link_convex_decomposition_p1.stl" />
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<mesh name="wrist_palm_link_fine" file="wrist_palm_link_fine.stl" />
<mesh name="wrist_palm_link_convex" file="wrist_palm_link_convex.stl" />
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<mesh name="cup12" file="cup_split12.stl" scale="0.001 0.001 0.001" />
<mesh name="cup13" file="cup_split13.stl" scale="0.001 0.001 0.001" />
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<mesh name="cup18" file="cup_split18.stl" scale="0.001 0.001 0.001" />
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<body name="B11" pos="0.0107 0 0">
<inertial pos="0 0 0" quat="0.707107 0 0.707107 0" mass="7.4927e-05" diaginertia="5.87e-10 5.87e-10 3.74635e-11" />
<joint name="J0_11" pos="-0.00535 0 0" axis="0 1 0" group="3" limited="false" damping="0.0001" frictionloss="0" />
<joint name="J1_11" pos="-0.00535 0 0" axis="0 0 1" group="3" limited="false" damping="0.0001" frictionloss="0" />
<geom name="G11" size="0.001 0.00427" quat="0.707107 0 0.707107 0" type="capsule" rgba="0.8 0.2 0.1 1" />
<body name="B12" pos="0.0107 0 0">
<inertial pos="0 0 0" quat="0.707107 0 0.707107 0" mass="7.4927e-05" diaginertia="5.87e-10 5.87e-10 3.74635e-11" />
<joint name="J0_12" pos="-0.00535 0 0" axis="0 1 0" group="3" limited="false" damping="0.0001" frictionloss="0" />
<joint name="J1_12" pos="-0.00535 0 0" axis="0 0 1" group="3" limited="false" damping="0.0001" frictionloss="0" />
<geom name="G12" size="0.001 0.00427" quat="0.707107 0 0.707107 0" type="capsule" rgba="0.8 0.2 0.1 1" />
<body name="B13" pos="0.0107 0 0">
<inertial pos="0 0 0" quat="0.707107 0 0.707107 0" mass="7.4927e-05" diaginertia="5.87e-10 5.87e-10 3.74635e-11" />
<joint name="J0_13" pos="-0.00535 0 0" axis="0 1 0" group="3" limited="false" damping="0.0001" frictionloss="0" />
<joint name="J1_13" pos="-0.00535 0 0" axis="0 0 1" group="3" limited="false" damping="0.0001" frictionloss="0" />
<geom name="G13" size="0.001 0.00427" quat="0.707107 0 0.707107 0" type="capsule" rgba="0.8 0.2 0.1 1" />
<body name="B14" pos="0.0107 0 0">
<inertial pos="0 0 0" quat="0.707107 0 0.707107 0" mass="7.4927e-05" diaginertia="5.87e-10 5.87e-10 3.74635e-11" />
<joint name="J0_14" pos="-0.00535 0 0" axis="0 1 0" group="3" limited="false" damping="0.0001" frictionloss="0" />
<joint name="J1_14" pos="-0.00535 0 0" axis="0 0 1" group="3" limited="false" damping="0.0001" frictionloss="0" />
<geom name="G14" size="0.001 0.00427" quat="0.707107 0 0.707107 0" type="capsule" rgba="0.8 0.2 0.1 1" />
<body name="B15" pos="0.0107 0 0">
<inertial pos="0 0 0" quat="0.707107 0 0.707107 0" mass="7.4927e-05" diaginertia="5.87e-10 5.87e-10 3.74635e-11" />
<joint name="J0_15" pos="-0.00535 0 0" axis="0 1 0" group="3" limited="false" damping="0.0001" frictionloss="0" />
<joint name="J1_15" pos="-0.00535 0 0" axis="0 0 1" group="3" limited="false" damping="0.0001" frictionloss="0" />
<geom name="G15" size="0.001 0.00427" quat="0.707107 0 0.707107 0" type="capsule" rgba="0.8 0.2 0.1 1" />
<body name="B16" pos="0.0107 0 0">
<inertial pos="0 0 0" quat="0.707107 0 0.707107 0" mass="7.4927e-05" diaginertia="5.87e-10 5.87e-10 3.74635e-11" />
<joint name="J0_16" pos="-0.00535 0 0" axis="0 1 0" group="3" limited="false" damping="0.0001" frictionloss="0" />
<joint name="J1_16" pos="-0.00535 0 0" axis="0 0 1" group="3" limited="false" damping="0.0001" frictionloss="0" />
<geom name="G16" size="0.001 0.00427" quat="0.707107 0 0.707107 0" type="capsule" rgba="0.8 0.2 0.1 1" />
<body name="B17" pos="0.0107 0 0">
<inertial pos="0 0 0" quat="0.707107 0 0.707107 0" mass="7.4927e-05" diaginertia="5.87e-10 5.87e-10 3.74635e-11" />
<joint name="J0_17" pos="-0.00535 0 0" axis="0 1 0" group="3" limited="false" damping="0.0001" frictionloss="0" />
<joint name="J1_17" pos="-0.00535 0 0" axis="0 0 1" group="3" limited="false" damping="0.0001" frictionloss="0" />
<geom name="G17" size="0.001 0.00427" quat="0.707107 0 0.707107 0" type="capsule" rgba="0.8 0.2 0.1 1" />
<body name="B18" pos="0.0107 0 0">
<inertial pos="0 0 0" quat="0.707107 0 0.707107 0" mass="7.4927e-05" diaginertia="5.87e-10 5.87e-10 3.74635e-11" />
<joint name="J0_18" pos="-0.00535 0 0" axis="0 1 0" group="3" limited="false" damping="0.0001" frictionloss="0" />
<joint name="J1_18" pos="-0.00535 0 0" axis="0 0 1" group="3" limited="false" damping="0.0001" frictionloss="0" />
<geom name="G18" size="0.001 0.00427" quat="0.707107 0 0.707107 0" type="capsule" rgba="0.8 0.2 0.1 1" />
<body name="B19" pos="0.0107 0 0">
<inertial pos="0 0 0" quat="0.707107 0 0.707107 0" mass="7.4927e-05" diaginertia="5.87e-10 5.87e-10 3.74635e-11" />
<joint name="J0_19" pos="-0.00535 0 0" axis="0 1 0" group="3" limited="false" damping="0.0001" frictionloss="0" />
<joint name="J1_19" pos="-0.00535 0 0" axis="0 0 1" group="3" limited="false" damping="0.0001" frictionloss="0" />
<geom name="G19" size="0.001 0.00427" quat="0.707107 0 0.707107 0" type="capsule" rgba="0.8 0.2 0.1 1" />
<body name="B20" pos="0.0107 0 0">
<inertial pos="0 0 0" quat="0.707107 0 0.707107 0" mass="7.4927e-05" diaginertia="5.87e-10 5.87e-10 3.74635e-11" />
<joint name="J0_20" pos="-0.00535 0 0" axis="0 1 0" group="3" limited="false" damping="0.0001" frictionloss="0" />
<joint name="J1_20" pos="-0.00535 0 0" axis="0 0 1" group="3" limited="false" damping="0.0001" frictionloss="0" />
<geom name="G20" size="0.001 0.00427" quat="0.707107 0 0.707107 0" type="capsule" rgba="0.8 0.2 0.1 1" />
<body name="B21" pos="0.0107 0 0">
<inertial pos="0 0 0" quat="0.707107 0 0.707107 0" mass="7.4927e-05" diaginertia="5.87e-10 5.87e-10 3.74635e-11" />
<joint name="J0_21" pos="-0.00535 0 0" axis="0 1 0" group="3" limited="false" damping="0.0001" frictionloss="0" />
<joint name="J1_21" pos="-0.00535 0 0" axis="0 0 1" group="3" limited="false" damping="0.0001" frictionloss="0" />
<geom name="G21" size="0.001 0.00427" quat="0.707107 0 0.707107 0" type="capsule" rgba="0.8 0.2 0.1 1" />
<body name="B22" pos="0.0107 0 0">
<inertial pos="0 0 0" quat="0.707107 0 0.707107 0" mass="7.4927e-05" diaginertia="5.87e-10 5.87e-10 3.74635e-11" />
<joint name="J0_22" pos="-0.00535 0 0" axis="0 1 0" group="3" limited="false" damping="0.0001" frictionloss="0" />
<joint name="J1_22" pos="-0.00535 0 0" axis="0 0 1" group="3" limited="false" damping="0.0001" frictionloss="0" />
<geom name="G22" size="0.001 0.00427" quat="0.707107 0 0.707107 0" type="capsule" rgba="0.8 0.2 0.1 1" />
<body name="B23" pos="0.0107 0 0">
<inertial pos="0 0 0" quat="0.707107 0 0.707107 0" mass="7.4927e-05" diaginertia="5.87e-10 5.87e-10 3.74635e-11" />
<joint name="J0_23" pos="-0.00535 0 0" axis="0 1 0" group="3" limited="false" damping="0.0001" frictionloss="0" />
<joint name="J1_23" pos="-0.00535 0 0" axis="0 0 1" group="3" limited="false" damping="0.0001" frictionloss="0" />
<geom name="G23" size="0.001 0.00427" quat="0.707107 0 0.707107 0" type="capsule" rgba="0.8 0.2 0.1 1" />
<body name="B24" pos="0.0107 0 0">
<inertial pos="0 0 0" quat="0.707107 0 0.707107 0" mass="7.4927e-05" diaginertia="5.87e-10 5.87e-10 3.74635e-11" />
<joint name="J0_24" pos="-0.00535 0 0" axis="0 1 0" group="3" limited="false" damping="0.0001" frictionloss="0" />
<joint name="J1_24" pos="-0.00535 0 0" axis="0 0 1" group="3" limited="false" damping="0.0001" frictionloss="0" />
<geom name="G24" size="0.001 0.00427" quat="0.707107 0 0.707107 0" type="capsule" rgba="0.8 0.2 0.1 1" />
<body name="B25" pos="0.0107 0 0">
<inertial pos="0 0 0" quat="0.707107 0 0.707107 0" mass="7.4927e-05" diaginertia="5.87e-10 5.87e-10 3.74635e-11" />
<joint name="J0_25" pos="-0.00535 0 0" axis="0 1 0" group="3" limited="false" damping="0.0001" frictionloss="0" />
<joint name="J1_25" pos="-0.00535 0 0" axis="0 0 1" group="3" limited="false" damping="0.0001" frictionloss="0" />
<geom name="G25" size="0.001 0.00427" quat="0.707107 0 0.707107 0" type="capsule" rgba="0.8 0.2 0.1 1" />
<body name="B26" pos="0.0107 0 0">
<inertial pos="0 0 0" quat="0.707107 0 0.707107 0" mass="7.4927e-05" diaginertia="5.87e-10 5.87e-10 3.74635e-11" />
<joint name="J0_26" pos="-0.00535 0 0" axis="0 1 0" group="3" limited="false" damping="0.0001" frictionloss="0" />
<joint name="J1_26" pos="-0.00535 0 0" axis="0 0 1" group="3" limited="false" damping="0.0001" frictionloss="0" />
<geom name="G26" size="0.001 0.00427" quat="0.707107 0 0.707107 0" type="capsule" rgba="0.8 0.2 0.1 1" />
<body name="B27" pos="0.0107 0 0">
<inertial pos="0 0 0" quat="0.707107 0 0.707107 0" mass="7.4927e-05" diaginertia="5.87e-10 5.87e-10 3.74635e-11" />
<joint name="J0_27" pos="-0.00535 0 0" axis="0 1 0" group="3" limited="false" damping="0.0001" frictionloss="0" />
<joint name="J1_27" pos="-0.00535 0 0" axis="0 0 1" group="3" limited="false" damping="0.0001" frictionloss="0" />
<geom name="G27" size="0.001 0.00427" quat="0.707107 0 0.707107 0" type="capsule" rgba="0.8 0.2 0.1 1" />
<body name="B28" pos="0.0107 0 0">
<inertial pos="0 0 0" quat="0.707107 0 0.707107 0" mass="7.4927e-05" diaginertia="5.87e-10 5.87e-10 3.74635e-11" />
<joint name="J0_28" pos="-0.00535 0 0" axis="0 1 0" group="3" limited="false" damping="0.0001" frictionloss="0" />
<joint name="J1_28" pos="-0.00535 0 0" axis="0 0 1" group="3" limited="false" damping="0.0001" frictionloss="0" />
<geom name="G28" size="0.001 0.00427" quat="0.707107 0 0.707107 0" type="capsule" rgba="0.8 0.2 0.1 1" />
<body name="B29" pos="0.0107 0 0">
<inertial pos="0 0 0" quat="0.707107 0 0.707107 0" mass="7.4927e-05" diaginertia="5.87e-10 5.87e-10 3.74635e-11" />
<joint name="J0_29" pos="-0.00535 0 0" axis="0 1 0" group="3" limited="false" damping="0.0001" frictionloss="0" />
<joint name="J1_29" pos="-0.00535 0 0" axis="0 0 1" group="3" limited="false" damping="0.0001" frictionloss="0" />
<geom name="G29" size="0.001 0.00427" quat="0.707107 0 0.707107 0" type="capsule" rgba="0.8 0.2 0.1 1" />
<body name="ball">
<geom name="ball_geom" type="sphere" size="0.02" mass="0.015" rgba="0.8 0.2 0.1 1"/>
</body>
</body>
</body>
</body>
</body>
</body>
</body>
</body>
</body>
</body>
</body>
</body>
</body>
</body>
</body>
</body>
</body>
</body>
</body>
</body>
</body>
</body>
</body>
</body>
</body>
</body>
</body>
</body>
</body>
</body>
</body>
</body>
</body>
</body>
</body>
</body>
</body>
</body>
</body>
</body>
<!-- <site name="context_point" pos="-0.20869846 -0.66376693 1.18088501" euler="-1.57 0 0" size="0.015" rgba="1 0 0 0.6" type="sphere"/>-->
<!-- <site name="context_point1" pos="-0.5 -0.85 0.8165" euler="-1.57 0 0" size="0.015" rgba="0 1 0 0.3" type="sphere"/>-->
<!-- <site name="context_point2" pos="-0.5 -0.85 1.4165" euler="-1.57 0 0" size="0.015" rgba="0 1 0 0.3" type="sphere"/>-->
<!-- <site name="context_point3" pos="-0.5 -0.35 0.8165" euler="-1.57 0 0" size="0.015" rgba="0 1 0 0.3" type="sphere"/>-->
<!-- <site name="context_point4" pos="-0.5 -0.35 1.4165" euler="-1.57 0 0" size="0.015" rgba="0 1 0 0.3" type="sphere"/>-->
<!-- <site name="context_point5" pos="0.5 -0.85 0.8165" euler="-1.57 0 0" size="0.015" rgba="0 1 0 0.3" type="sphere"/>-->
<!-- <site name="context_point6" pos="0.5 -0.85 1.4165" euler="-1.57 0 0" size="0.015" rgba="0 1 0 0.3" type="sphere"/>-->
<!-- <site name="context_point7" pos="0.5 -0.35 0.8165" euler="-1.57 0 0" size="0.015" rgba="0 1 0 0.3" type="sphere"/>-->
<!-- <site name="context_point8" pos="0.5 -0.35 1.4165" euler="-1.57 0 0" size="0.015" rgba="0 1 0 0.3" type="sphere"/>-->
<!-- <site name="context_space" pos="0 -0.6 1.1165" euler="0 0 0" size="0.5 0.25 0.3" rgba="0 0 1 0.15" type="box"/>-->
<camera name="visualization" mode="targetbody" target="wam/wrist_yaw_link" pos="1.5 -0.4 2.2"/>
<camera name="experiment" mode="fixed" quat="0.44418059 0.41778323 0.54301123 0.57732103" pos="1.5 -0.3 1.33" />
</worldbody>
<actuator>
<!-- <motor ctrllimited="true" ctrlrange="-150 150" joint="wam/base_yaw_joint"/>-->
<!-- <motor ctrllimited="true" ctrlrange="-125 125" joint="wam/shoulder_pitch_joint"/>-->
<!-- <motor ctrllimited="true" ctrlrange="-40 40" joint="wam/shoulder_yaw_joint"/>-->
<!-- <motor ctrllimited="true" ctrlrange="-60 60" joint="wam/elbow_pitch_joint"/>-->
<!-- <motor ctrllimited="true" ctrlrange="-5 5" joint="wam/wrist_yaw_joint"/>-->
<!-- <motor ctrllimited="true" ctrlrange="-5 5" joint="wam/wrist_pitch_joint"/>-->
<!-- <motor ctrllimited="true" ctrlrange="-2 2" joint="wam/palm_yaw_joint"/>-->
<motor ctrllimited="true" ctrlrange="-1.0 1.0" gear="150.0" joint="wam/base_yaw_joint"/>
<motor ctrllimited="true" ctrlrange="-1.0 1.0" gear="125.0" joint="wam/shoulder_pitch_joint"/>
<motor ctrllimited="true" ctrlrange="-1.0 1.0" gear="40.0" joint="wam/shoulder_yaw_joint"/>
<motor ctrllimited="true" ctrlrange="-1.0 1.0" gear="60.0" joint="wam/elbow_pitch_joint"/>
<motor ctrllimited="true" ctrlrange="-1.0 1.0" gear="5.0" joint="wam/wrist_yaw_joint"/>
<motor ctrllimited="true" ctrlrange="-1.0 1.0" gear="5.0" joint="wam/wrist_pitch_joint"/>
<motor ctrllimited="true" ctrlrange="-1.0 1.0" gear="2.0" joint="wam/palm_yaw_joint"/>
</actuator>
</mujoco>

View File

@ -1,195 +0,0 @@
from gym import utils
import os
import numpy as np
from gym.envs.mujoco import MujocoEnv
class ALRBallInACupEnv(MujocoEnv, utils.EzPickle):
def __init__(
self, n_substeps=4, apply_gravity_comp=True, simplified: bool = False,
reward_type: str = None, context: np.ndarray = None
):
utils.EzPickle.__init__(**locals())
self._steps = 0
self.xml_path = os.path.join(os.path.dirname(os.path.abspath(__file__)), "assets", "biac_base.xml")
self._q_pos = []
self._q_vel = []
# self.weight_matrix_scale = 50
self.max_ctrl = np.array([150., 125., 40., 60., 5., 5., 2.])
self.j_min = np.array([-2.6, -1.985, -2.8, -0.9, -4.55, -1.5707, -2.7])
self.j_max = np.array([2.6, 1.985, 2.8, 3.14159, 1.25, 1.5707, 2.7])
self.context = context
alr_mujoco_env.AlrMujocoEnv.__init__(self, self.xml_path, apply_gravity_comp=apply_gravity_comp,
n_substeps=n_substeps)
self._start_pos = np.array([0.0, 0.58760536, 0.0, 1.36004913, 0.0, -0.32072943, -1.57])
self._start_vel = np.zeros(7)
self.simplified = simplified
self.sim_time = 8 # seconds
self.sim_steps = int(self.sim_time / self.dt)
if reward_type == "no_context":
from alr_envs.alr.mujoco.ball_in_a_cup.ball_in_a_cup_reward_simple import BallInACupReward
reward_function = BallInACupReward
elif reward_type == "contextual_goal":
from alr_envs.alr.mujoco.ball_in_a_cup.ball_in_a_cup_reward import BallInACupReward
reward_function = BallInACupReward
else:
raise ValueError("Unknown reward type: {}".format(reward_type))
self.reward_function = reward_function(self.sim_steps)
@property
def start_pos(self):
if self.simplified:
return self._start_pos[1::2]
else:
return self._start_pos
@property
def start_vel(self):
if self.simplified:
return self._start_vel[1::2]
else:
return self._start_vel
@property
def current_pos(self):
return self.sim.data.qpos[0:7].copy()
@property
def current_vel(self):
return self.sim.data.qvel[0:7].copy()
def reset(self):
self.reward_function.reset(None)
return super().reset()
def reset_model(self):
init_pos_all = self.init_qpos.copy()
init_pos_robot = self._start_pos
init_vel = np.zeros_like(init_pos_all)
self._steps = 0
self._q_pos = []
self._q_vel = []
start_pos = init_pos_all
start_pos[0:7] = init_pos_robot
self.set_state(start_pos, init_vel)
return self._get_obs()
def step(self, a):
reward_dist = 0.0
angular_vel = 0.0
reward_ctrl = - np.square(a).sum()
crash = self.do_simulation(a)
# joint_cons_viol = self.check_traj_in_joint_limits()
self._q_pos.append(self.sim.data.qpos[0:7].ravel().copy())
self._q_vel.append(self.sim.data.qvel[0:7].ravel().copy())
ob = self._get_obs()
if not crash:
reward, success, is_collided = self.reward_function.compute_reward(a, self)
done = success or self._steps == self.sim_steps - 1 or is_collided
self._steps += 1
else:
reward = -2000
success = False
is_collided = False
done = True
return ob, reward, done, dict(reward_dist=reward_dist,
reward_ctrl=reward_ctrl,
velocity=angular_vel,
# traj=self._q_pos,
action=a,
q_pos=self.sim.data.qpos[0:7].ravel().copy(),
q_vel=self.sim.data.qvel[0:7].ravel().copy(),
is_success=success,
is_collided=is_collided, sim_crash=crash)
def check_traj_in_joint_limits(self):
return any(self.current_pos > self.j_max) or any(self.current_pos < self.j_min)
# TODO: extend observation space
def _get_obs(self):
theta = self.sim.data.qpos.flat[:7]
return np.concatenate([
np.cos(theta),
np.sin(theta),
# self.get_body_com("target"), # only return target to make problem harder
[self._steps],
])
# TODO
@property
def active_obs(self):
return np.hstack([
[False] * 7, # cos
[False] * 7, # sin
# [True] * 2, # x-y coordinates of target distance
[False] # env steps
])
# These functions are for the task with 3 joint actuations
def extend_des_pos(self, des_pos):
des_pos_full = self._start_pos.copy()
des_pos_full[1] = des_pos[0]
des_pos_full[3] = des_pos[1]
des_pos_full[5] = des_pos[2]
return des_pos_full
def extend_des_vel(self, des_vel):
des_vel_full = self._start_vel.copy()
des_vel_full[1] = des_vel[0]
des_vel_full[3] = des_vel[1]
des_vel_full[5] = des_vel[2]
return des_vel_full
def render(self, render_mode, **render_kwargs):
if render_mode == "plot_trajectory":
if self._steps == 1:
import matplotlib.pyplot as plt
# plt.ion()
self.fig, self.axs = plt.subplots(3, 1)
if self._steps <= 1750:
for ax, cp in zip(self.axs, self.current_pos[1::2]):
ax.scatter(self._steps, cp, s=2, marker=".")
# self.fig.show()
else:
super().render(render_mode, **render_kwargs)
if __name__ == "__main__":
env = ALRBallInACupEnv()
ctxt = np.array([-0.20869846, -0.66376693, 1.18088501])
env.configure(ctxt)
env.reset()
# env.render()
for i in range(16000):
# test with random actions
ac = 0.001 * env.action_space.sample()[0:7]
# ac = env.start_pos
# ac[0] += np.pi/2
obs, rew, d, info = env.step(ac)
# env.render()
print(rew)
if d:
break
env.close()

View File

@ -1,42 +0,0 @@
from typing import Tuple, Union
import numpy as np
from alr_envs.black_box.raw_interface_wrapper import RawInterfaceWrapper
class BallInACupMPWrapper(RawInterfaceWrapper):
@property
def context_mask(self) -> np.ndarray:
# TODO: @Max Filter observations correctly
return np.hstack([
[False] * 7, # cos
[False] * 7, # sin
# [True] * 2, # x-y coordinates of target distance
[False] # env steps
])
@property
def start_pos(self):
if self.simplified:
return self._start_pos[1::2]
else:
return self._start_pos
@property
def current_pos(self) -> Union[float, int, np.ndarray, Tuple]:
return self.sim.data.qpos[0:7].copy()
@property
def current_vel(self) -> Union[float, int, np.ndarray, Tuple]:
return self.sim.data.qvel[0:7].copy()
@property
def goal_pos(self):
# TODO: @Max I think the default value of returning to the start is reasonable here
raise ValueError("Goal position is not available and has to be learnt based on the environment.")
@property
def dt(self) -> Union[float, int]:
return self.env.dt

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import numpy as np
from alr_envs.alr.mujoco.ball_in_a_cup import alr_reward_fct
class BallInACupReward(alr_reward_fct.AlrReward):
def __init__(self, sim_time):
self.sim_time = sim_time
self.collision_objects = ["cup_geom1", "cup_geom2", "wrist_palm_link_convex_geom",
"wrist_pitch_link_convex_decomposition_p1_geom",
"wrist_pitch_link_convex_decomposition_p2_geom",
"wrist_pitch_link_convex_decomposition_p3_geom",
"wrist_yaw_link_convex_decomposition_p1_geom",
"wrist_yaw_link_convex_decomposition_p2_geom",
"forearm_link_convex_decomposition_p1_geom",
"forearm_link_convex_decomposition_p2_geom"]
self.ball_id = None
self.ball_collision_id = None
self.goal_id = None
self.goal_final_id = None
self.collision_ids = None
self.ball_traj = None
self.dists = None
self.dists_ctxt = None
self.dists_final = None
self.costs = None
self.reset(None)
def reset(self, context):
self.ball_traj = np.zeros(shape=(self.sim_time, 3))
self.cup_traj = np.zeros(shape=(self.sim_time, 3))
self.dists = []
self.dists_ctxt = []
self.dists_final = []
self.costs = []
self.context = context
self.ball_in_cup = False
self.ball_above_threshold = False
self.dist_ctxt = 3
self.action_costs = []
self.cup_angles = []
def compute_reward(self, action, sim, step):
action_cost = np.sum(np.square(action))
self.action_costs.append(action_cost)
stop_sim = False
success = False
self.ball_id = sim.model._body_name2id["ball"]
self.ball_collision_id = sim.model._geom_name2id["ball_geom"]
self.goal_id = sim.model._site_name2id["cup_goal"]
self.goal_final_id = sim.model._site_name2id["cup_goal_final"]
self.collision_ids = [sim.model._geom_name2id[name] for name in self.collision_objects]
if self.check_collision(sim):
reward = - 1e-3 * action_cost - 1000
stop_sim = True
return reward, success, stop_sim
# Compute the current distance from the ball to the inner part of the cup
goal_pos = sim.data.site_xpos[self.goal_id]
ball_pos = sim.data.body_xpos[self.ball_id]
goal_final_pos = sim.data.site_xpos[self.goal_final_id]
self.dists.append(np.linalg.norm(goal_pos - ball_pos))
self.dists_final.append(np.linalg.norm(goal_final_pos - ball_pos))
self.dists_ctxt.append(np.linalg.norm(ball_pos - self.context))
self.ball_traj[step, :] = np.copy(ball_pos)
self.cup_traj[step, :] = np.copy(goal_pos) # ?
cup_quat = np.copy(sim.data.body_xquat[sim.model._body_name2id["cup"]])
self.cup_angles.append(np.arctan2(2 * (cup_quat[0] * cup_quat[1] + cup_quat[2] * cup_quat[3]),
1 - 2 * (cup_quat[1] ** 2 + cup_quat[2] ** 2)))
# Determine the first time when ball is in cup
if not self.ball_in_cup:
ball_in_cup = self.check_ball_in_cup(sim, self.ball_collision_id)
self.ball_in_cup = ball_in_cup
if ball_in_cup:
dist_to_ctxt = np.linalg.norm(ball_pos - self.context)
self.dist_ctxt = dist_to_ctxt
if step == self.sim_time - 1:
t_min_dist = np.argmin(self.dists)
angle_min_dist = self.cup_angles[t_min_dist]
cost_angle = (angle_min_dist - np.pi / 2) ** 2
min_dist = np.min(self.dists)
dist_final = self.dists_final[-1]
# dist_ctxt = self.dists_ctxt[-1]
# # max distance between ball and cup and cup height at that time
# ball_to_cup_diff = self.ball_traj[:, 2] - self.cup_traj[:, 2]
# t_max_diff = np.argmax(ball_to_cup_diff)
# t_max_ball_height = np.argmax(self.ball_traj[:, 2])
# max_ball_height = np.max(self.ball_traj[:, 2])
# cost = self._get_stage_wise_cost(ball_in_cup, min_dist, dist_final, dist_ctxt)
cost = 0.5 * min_dist + 0.5 * dist_final + 0.3 * np.minimum(self.dist_ctxt, 3) + 0.01 * cost_angle
reward = np.exp(-2 * cost) - 1e-3 * action_cost
# if max_ball_height < self.context[2] or ball_to_cup_diff[t_max_ball_height] < 0:
# reward -= 1
success = dist_final < 0.05 and self.dist_ctxt < 0.05
else:
reward = - 1e-3 * action_cost
success = False
return reward, success, stop_sim
def _get_stage_wise_cost(self, ball_in_cup, min_dist, dist_final, dist_to_ctxt):
if not ball_in_cup:
cost = 3 + 2*(0.5 * min_dist**2 + 0.5 * dist_final**2)
else:
cost = 2 * dist_to_ctxt ** 2
print('Context Distance:', dist_to_ctxt)
return cost
def check_ball_in_cup(self, sim, ball_collision_id):
cup_base_collision_id = sim.model._geom_name2id["cup_base_contact"]
for coni in range(0, sim.data.ncon):
con = sim.data.contact[coni]
collision = con.geom1 == cup_base_collision_id and con.geom2 == ball_collision_id
collision_trans = con.geom1 == ball_collision_id and con.geom2 == cup_base_collision_id
if collision or collision_trans:
return True
return False
def check_collision(self, sim):
for coni in range(0, sim.data.ncon):
con = sim.data.contact[coni]
collision = con.geom1 in self.collision_ids and con.geom2 == self.ball_collision_id
collision_trans = con.geom1 == self.ball_collision_id and con.geom2 in self.collision_ids
if collision or collision_trans:
return True
return False

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@ -1,116 +0,0 @@
import numpy as np
from alr_envs.alr.mujoco.ball_in_a_cup import alr_reward_fct
class BallInACupReward(alr_reward_fct.AlrReward):
def __init__(self, env):
self.env = env
self.collision_objects = ["cup_geom1", "cup_geom2", "cup_base_contact_below",
"wrist_palm_link_convex_geom",
"wrist_pitch_link_convex_decomposition_p1_geom",
"wrist_pitch_link_convex_decomposition_p2_geom",
"wrist_pitch_link_convex_decomposition_p3_geom",
"wrist_yaw_link_convex_decomposition_p1_geom",
"wrist_yaw_link_convex_decomposition_p2_geom",
"forearm_link_convex_decomposition_p1_geom",
"forearm_link_convex_decomposition_p2_geom"]
self.ball_id = None
self.ball_collision_id = None
self.goal_id = None
self.goal_final_id = None
self.collision_ids = None
self._is_collided = False
self.collision_penalty = 1000
self.ball_traj = None
self.dists = None
self.dists_final = None
self.costs = None
self.reset(None)
def reset(self, context):
# self.sim_time = self.env.sim.dtsim_time
self.ball_traj = [] # np.zeros(shape=(self.sim_time, 3))
self.dists = []
self.dists_final = []
self.costs = []
self.action_costs = []
self.angle_costs = []
self.cup_angles = []
def compute_reward(self, action):
self.ball_id = self.env.sim.model._body_name2id["ball"]
self.ball_collision_id = self.env.sim.model._geom_name2id["ball_geom"]
self.goal_id = self.env.sim.model._site_name2id["cup_goal"]
self.goal_final_id = self.env.sim.model._site_name2id["cup_goal_final"]
self.collision_ids = [self.env.sim.model._geom_name2id[name] for name in self.collision_objects]
ball_in_cup = self.check_ball_in_cup(self.env.sim, self.ball_collision_id)
# Compute the current distance from the ball to the inner part of the cup
goal_pos = self.env.sim.data.site_xpos[self.goal_id]
ball_pos = self.env.sim.data.body_xpos[self.ball_id]
goal_final_pos = self.env.sim.data.site_xpos[self.goal_final_id]
self.dists.append(np.linalg.norm(goal_pos - ball_pos))
self.dists_final.append(np.linalg.norm(goal_final_pos - ball_pos))
# self.ball_traj[self.env._steps, :] = ball_pos
self.ball_traj.append(ball_pos)
cup_quat = np.copy(self.env.sim.data.body_xquat[self.env.sim.model._body_name2id["cup"]])
cup_angle = np.arctan2(2 * (cup_quat[0] * cup_quat[1] + cup_quat[2] * cup_quat[3]),
1 - 2 * (cup_quat[1]**2 + cup_quat[2]**2))
cost_angle = (cup_angle - np.pi / 2) ** 2
self.angle_costs.append(cost_angle)
self.cup_angles.append(cup_angle)
action_cost = np.sum(np.square(action))
self.action_costs.append(action_cost)
self._is_collided = self.check_collision(self.env.sim) or self.env._check_traj_in_joint_limits()
if self.env._steps == self.env.ep_length - 1 or self._is_collided:
t_min_dist = np.argmin(self.dists)
angle_min_dist = self.cup_angles[t_min_dist]
# cost_angle = (angle_min_dist - np.pi / 2)**2
# min_dist = self.dists[t_min_dist]
dist_final = self.dists_final[-1]
min_dist_final = np.min(self.dists_final)
# cost = 0.5 * dist_final + 0.05 * cost_angle # TODO: Increase cost_angle weight # 0.5 * min_dist +
# reward = np.exp(-2 * cost) - 1e-2 * action_cost - self.collision_penalty * int(self._is_collided)
# reward = - dist_final**2 - 1e-4 * cost_angle - 1e-5 * action_cost - self.collision_penalty * int(self._is_collided)
reward = - dist_final**2 - min_dist_final**2 - 1e-4 * cost_angle - 1e-3 * action_cost - self.collision_penalty * int(self._is_collided)
success = dist_final < 0.05 and ball_in_cup and not self._is_collided
crash = self._is_collided
else:
reward = - 1e-3 * action_cost - 1e-4 * cost_angle # TODO: increase action_cost weight
success = False
crash = False
return reward, success, crash
def check_ball_in_cup(self, sim, ball_collision_id):
cup_base_collision_id = sim.model._geom_name2id["cup_base_contact"]
for coni in range(0, sim.data.ncon):
con = sim.data.contact[coni]
collision = con.geom1 == cup_base_collision_id and con.geom2 == ball_collision_id
collision_trans = con.geom1 == ball_collision_id and con.geom2 == cup_base_collision_id
if collision or collision_trans:
return True
return False
def check_collision(self, sim):
for coni in range(0, sim.data.ncon):
con = sim.data.contact[coni]
collision = con.geom1 in self.collision_ids and con.geom2 == self.ball_collision_id
collision_trans = con.geom1 == self.ball_collision_id and con.geom2 in self.collision_ids
if collision or collision_trans:
return True
return False

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import os
import gym.envs.mujoco
import gym.envs.mujoco as mujoco_env
import mujoco_py.builder
import numpy as np
from gym import utils
class ALRBallInACupPDEnv(mujoco_env.MujocoEnv, utils.EzPickle):
def __init__(self, frame_skip=4, apply_gravity_comp=True, simplified: bool = False,
reward_type: str = None, context: np.ndarray = None):
utils.EzPickle.__init__(**locals())
self._steps = 0
self.xml_path = os.path.join(os.path.dirname(os.path.abspath(__file__)), "assets", "biac_base.xml")
self.max_ctrl = np.array([150., 125., 40., 60., 5., 5., 2.])
self.j_min = np.array([-2.6, -1.985, -2.8, -0.9, -4.55, -1.5707, -2.7])
self.j_max = np.array([2.6, 1.985, 2.8, 3.14159, 1.25, 1.5707, 2.7])
self.context = context
self.apply_gravity_comp = apply_gravity_comp
self.simplified = simplified
self._start_pos = np.array([0.0, 0.58760536, 0.0, 1.36004913, 0.0, -0.32072943, -1.57])
self._start_vel = np.zeros(7)
self.sim_time = 8 # seconds
self._dt = 0.02
self.ep_length = 4000 # based on 8 seconds with dt = 0.02 int(self.sim_time / self.dt)
if reward_type == "no_context":
from alr_envs.alr.mujoco.ball_in_a_cup.ball_in_a_cup_reward_simple import BallInACupReward
reward_function = BallInACupReward
elif reward_type == "contextual_goal":
from alr_envs.alr.mujoco.ball_in_a_cup.ball_in_a_cup_reward import BallInACupReward
reward_function = BallInACupReward
else:
raise ValueError("Unknown reward type: {}".format(reward_type))
self.reward_function = reward_function(self)
mujoco_env.MujocoEnv.__init__(self, self.xml_path, frame_skip)
@property
def dt(self):
return self._dt
# TODO: @Max is this even needed?
@property
def start_vel(self):
if self.simplified:
return self._start_vel[1::2]
else:
return self._start_vel
# def _set_action_space(self):
# if self.simplified:
# bounds = self.model.actuator_ctrlrange.copy().astype(np.float32)[1::2]
# else:
# bounds = self.model.actuator_ctrlrange.copy().astype(np.float32)
# low, high = bounds.T
# self.action_space = spaces.Box(low=low, high=high, dtype=np.float32)
# return self.action_space
def reset(self):
self.reward_function.reset(None)
return super().reset()
def reset_model(self):
init_pos_all = self.init_qpos.copy()
init_pos_robot = self._start_pos
init_vel = np.zeros_like(init_pos_all)
self._steps = 0
self._q_pos = []
self._q_vel = []
start_pos = init_pos_all
start_pos[0:7] = init_pos_robot
self.set_state(start_pos, init_vel)
return self._get_obs()
def step(self, a):
reward_dist = 0.0
angular_vel = 0.0
reward_ctrl = - np.square(a).sum()
# if self.simplified:
# tmp = np.zeros(7)
# tmp[1::2] = a
# a = tmp
if self.apply_gravity_comp:
a += self.sim.data.qfrc_bias[:len(a)].copy() / self.model.actuator_gear[:, 0]
crash = False
try:
self.do_simulation(a, self.frame_skip)
except mujoco_py.builder.MujocoException:
crash = True
# joint_cons_viol = self.check_traj_in_joint_limits()
ob = self._get_obs()
if not crash:
reward, success, is_collided = self.reward_function.compute_reward(a)
done = success or is_collided # self._steps == self.sim_steps - 1
self._steps += 1
else:
reward = -2000
success = False
is_collided = False
done = True
return ob, reward, done, dict(reward_dist=reward_dist,
reward_ctrl=reward_ctrl,
velocity=angular_vel,
# traj=self._q_pos,
action=a,
q_pos=self.sim.data.qpos[0:7].ravel().copy(),
q_vel=self.sim.data.qvel[0:7].ravel().copy(),
is_success=success,
is_collided=is_collided, sim_crash=crash)
def check_traj_in_joint_limits(self):
return any(self.current_pos > self.j_max) or any(self.current_pos < self.j_min)
# TODO: extend observation space
def _get_obs(self):
theta = self.sim.data.qpos.flat[:7]
return np.concatenate([
np.cos(theta),
np.sin(theta),
# self.get_body_com("target"), # only return target to make problem harder
[self._steps],
])
# These functions are for the task with 3 joint actuations
def extend_des_pos(self, des_pos):
des_pos_full = self._start_pos.copy()
des_pos_full[1] = des_pos[0]
des_pos_full[3] = des_pos[1]
des_pos_full[5] = des_pos[2]
return des_pos_full
def extend_des_vel(self, des_vel):
des_vel_full = self._start_vel.copy()
des_vel_full[1] = des_vel[0]
des_vel_full[3] = des_vel[1]
des_vel_full[5] = des_vel[2]
return des_vel_full
def render(self, render_mode, **render_kwargs):
if render_mode == "plot_trajectory":
if self._steps == 1:
import matplotlib.pyplot as plt
# plt.ion()
self.fig, self.axs = plt.subplots(3, 1)
if self._steps <= 1750:
for ax, cp in zip(self.axs, self.current_pos[1::2]):
ax.scatter(self._steps, cp, s=2, marker=".")
# self.fig.show()
else:
super().render(render_mode, **render_kwargs)
if __name__ == "__main__":
env = ALRBallInACupPDEnv(reward_type="no_context", simplified=True)
# env = gym.make("alr_envs:ALRBallInACupPDSimpleDetPMP-v0")
# ctxt = np.array([-0.20869846, -0.66376693, 1.18088501])
# env.configure(ctxt)
env.reset()
env.render("human")
for i in range(16000):
# test with random actions
ac = 0.02 * env.action_space.sample()[0:7]
# ac = env.start_pos
# ac[0] += np.pi/2
obs, rew, d, info = env.step(ac)
env.render("human")
print(rew)
if d:
break
env.close()

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@ -1,42 +0,0 @@
from typing import Union, Tuple
import numpy as np
from alr_envs.black_box.raw_interface_wrapper import RawInterfaceWrapper
class MPWrapper(RawInterfaceWrapper):
def get_context_mask(self):
return np.hstack([
[False] * 7, # cos
[False] * 7, # sin
[False] * 7, # joint velocities
[False] * 3, # cup_goal_diff_final
[False] * 3, # cup_goal_diff_top
[True] * 2, # xy position of cup
[False] # env steps
])
@property
def current_pos(self) -> Union[float, int, np.ndarray, Tuple]:
return self.env.sim.data.qpos[0:7].copy()
@property
def current_vel(self) -> Union[float, int, np.ndarray, Tuple]:
return self.env.sim.data.qvel[0:7].copy()
# TODO: Fix this
def _episode_callback(self, action: np.ndarray, mp) -> Tuple[np.ndarray, Union[np.ndarray, None]]:
if mp.learn_tau:
self.env.env.release_step = action[0] / self.env.dt # Tau value
return action, None
else:
return action, None
def set_context(self, context):
xyz = np.zeros(3)
xyz[:2] = context
xyz[-1] = 0.840
self.env.env.model.body_pos[self.env.env.cup_table_id] = xyz
return self.get_observation_from_step(self.env.env._get_obs())

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@ -1,12 +0,0 @@
<mujocoinclude>
<actuator boastype="none">
<motor name="wam/shoulder_yaw_link_right_motor" joint="wam/base_yaw_joint_right"/>
<motor name="wam/shoulder_pitch_joint_right_motor" joint='wam/shoulder_pitch_joint_right'/>
<motor name="wam/shoulder_yaw_joint_right_motor" joint='wam/shoulder_yaw_joint_right'/>
<motor name="wam/elbow_pitch_joint_right_motor" joint='wam/elbow_pitch_joint_right'/>
<motor name="wam/wrist_yaw_joint_right_motor" joint='wam/wrist_yaw_joint_right'/>
<motor name="wam/wrist_pitch_joint_right_motor" joint='wam/wrist_pitch_joint_right'/>
<motor name="wam/palm_yaw_joint_right_motor" joint='wam/palm_yaw_joint_right'/>
</actuator>
</mujocoinclude>

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@ -1,76 +0,0 @@
<mujocoinclude>
<body name="wam/base_link_left" pos="-2.5 0 2" quat="0 1 0 0" childclass="wam">
<inertial pos="0 0 0" mass="1" diaginertia="0.1 0.1 0.1"/>
<geom class="viz" mesh="base_link_fine" rgba="0.5 0.5 0.5 0"/>
<geom class="col" mesh="base_link_convex" rgba="0.5 0.5 0.5 1"/>
<body name="wam/shoulder_yaw_link" pos="0 0 0.346">
<inertial pos="-0.00443422 -0.00066489 -0.128904" quat="0.69566 0.716713 -0.0354863 0.0334839" mass="5"
diaginertia="0.135089 0.113095 0.0904426"/>
<joint name="wam/base_yaw_joint" range="-2.6 2.6" damping="1.98"/>
<geom class="viz" mesh="shoulder_link_fine" rgba="1 1 1 0"/>
<geom class="col" mesh="shoulder_link_convex_decomposition_p1"/>
<geom class="col" mesh="shoulder_link_convex_decomposition_p2"/>
<geom class="col" mesh="shoulder_link_convex_decomposition_p3"/>
<body name="wam/shoulder_pitch_link" pos="0 0 0" quat="0.707107 -0.707107 0 0">
<inertial pos="-0.00236981 -0.0154211 0.0310561" quat="0.961794 0.273112 -0.0169316 0.00866592"
mass="3.87494" diaginertia="0.0214195 0.0167127 0.0126452"/> <!--seems off-->
<joint name="wam/shoulder_pitch_joint" range="-1.985 1.985" damping="0.55"/>
<geom class="viz" mesh="shoulder_pitch_link_fine" rgba="1 1 1 0"/>
<geom class="col" mesh="shoulder_pitch_link_convex"/>
<body name="wam/upper_arm_link" pos="0 0 0" quat="0.707107 0.707107 0 0">
<inertial pos="0.00683259 3.309e-005 0.392492" quat="0.647136 0.0170822 0.0143038 0.762049"
mass="2.20228" diaginertia="0.0592718 0.0592207 0.00313419"/>
<joint name="wam/shoulder_yaw_joint" range="-2.8 2.8" damping="1.65"/>
<geom class="viz" mesh="upper_arm_link_fine" rgba="1 1 1 0"/>
<geom class="col" mesh="upper_arm_link_convex_decomposition_p1" rgba="0.094 0.48 0.804 1"/>
<geom class="col" mesh="upper_arm_link_convex_decomposition_p2" rgba="0.094 0.48 0.804 1"/>
<body name="wam/forearm_link" pos="0.045 0 0.55" quat="0.707107 -0.707107 0 0">
<inertial pos="-0.0400149 -0.142717 -0.00022942"
quat="0.704281 0.706326 0.0180333 0.0690353" mass="0.500168"
diaginertia="0.0151047 0.0148285 0.00275805"/>
<joint name="wam/elbow_pitch_joint" range="-0.9 3.14159" damping="0.88"/>
<geom class="viz" mesh="elbow_link_fine" rgba="1 1 1 0"/>
<geom class="col" mesh="elbow_link_convex"/>
<geom class="viz" mesh="forearm_link_fine" pos="-.045 -0.0730 0" euler="1.57 0 0" rgba="1 1 1 0"/>
<geom class="col" mesh="forearm_link_convex_decomposition_p1" pos="-0.045 -0.0730 0"
euler="1.57 0 0" rgba="0.094 0.48 0.804 1"/>
<geom class="col" mesh="forearm_link_convex_decomposition_p2" pos="-.045 -0.0730 0"
euler="1.57 0 0" rgba="0.094 0.48 0.804 1"/>
<body name="wam/wrist_yaw_link" pos="-0.045 -0.3 0" quat="0.707107 0.707107 0 0">
<inertial pos="8.921e-005 0.00435824 -0.00511217"
quat="0.630602 0.776093 0.00401969 -0.002372" mass="1.05376"
diaginertia="0.000555168 0.00046317 0.000234072"/> <!--this is an approximation-->
<joint name="wam/wrist_yaw_joint" range="-4.55 1.25" damping="0.55"/>
<geom class="viz" mesh="wrist_yaw_link_fine" rgba="1 1 1 0"/>
<geom class="col" mesh="wrist_yaw_link_convex_decomposition_p1"/>
<geom class="col" mesh="wrist_yaw_link_convex_decomposition_p2"/>
<body name="wam/wrist_pitch_link" pos="0 0 0" quat="0.707107 -0.707107 0 0">
<inertial pos="-0.00012262 -0.0246834 -0.0170319"
quat="0.630602 0.776093 0.00401969 -0.002372" mass="0.517974"
diaginertia="0.000555168 0.00046317 0.000234072"/>
<joint name="wam/wrist_pitch_joint" range="-1.5707 1.5707" damping="0.11"/>
<geom class="viz" mesh="wrist_pitch_link_fine" rgba="1 1 1 0"/>
<geom class="col" mesh="wrist_pitch_link_convex_decomposition_p1" rgba="1 0.5 0.313 1"/>
<geom class="col" mesh="wrist_pitch_link_convex_decomposition_p2" rgba="1 0.5 0.313 1"/>
<geom class="col" mesh="wrist_pitch_link_convex_decomposition_p3" rgba="1 0.5 0.313 1"/>
<body name="wam/wrist_palm_link" pos="0 0 0" quat="0.707107 0.707107 0 0">
<inertial pos="0 0 0.055" quat="0.707107 0 0 0.707107" mass="0.0828613"
diaginertia="0.00020683 0.00010859 0.00010851"/>
<joint name="wam/palm_yaw_joint" range="-3 3" damping="0.11"/>
<geom class="viz" mesh="wrist_palm_link_fine" rgba="1 1 1 0"/>
<geom class="col" mesh="wrist_palm_link_convex"/>
<body name="paddle_left" pos="0 0 0.26" childclass="contact_geom">
<geom name="bat_left" type="cylinder" size="0.075 0.0015" rgba="1 0 0 1"
quat="0.71 0 0.71 0"/>
<geom name="handle_left" type="box" size="0.005 0.01 0.05" pos="0 0 -0.08"
rgba="1 1 1 1"/>
</body>
</body>
</body>
</body>
</body>
</body>
</body>
</body>
</body>
</mujocoinclude>

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@ -1,95 +0,0 @@
<mujocoinclue>
<body name="wam/base_link_right" pos="2.5 0 2" quat="0 0 1 0" childclass="wam" >
<inertial pos="0 0 0" mass="1" diaginertia="0.1 0.1 0.1"/>
<geom name="base_link_fine" class="viz" mesh="base_link_fine" rgba="0.5 0.5 0.5 0"/>
<geom name="base_link_convex" class="col" mesh="base_link_convex" rgba="0.5 0.5 0.5 1"/>
<body name="wam/shoulder_yaw_link_right" pos="0 0 0.346">
<inertial pos="-0.00443422 -0.00066489 -0.128904" quat="0.69566 0.716713 -0.0354863 0.0334839" mass="5"
diaginertia="0.135089 0.113095 0.0904426"/>
<joint name="wam/base_yaw_joint_right" range="-2.6 2.6" damping="1.98"/>
<geom name="shoulder_link_fine" class="viz" mesh="shoulder_link_fine" rgba="1 1 1 0"/>
<geom name="shoulder_link_convex_decomposition_p1" class="col"
mesh="shoulder_link_convex_decomposition_p1"/>
<geom name="shoulder_link_convex_decomposition_p2" class="col"
mesh="shoulder_link_convex_decomposition_p2"/>
<geom name="shoulder_link_convex_decomposition_p3" class="col"
mesh="shoulder_link_convex_decomposition_p3"/>
<body name="wam/shoulder_pitch_link_right" pos="0 0 0" quat="0.707107 -0.707107 0 0">
<inertial pos="-0.00236981 -0.0154211 0.0310561" quat="0.961794 0.273112 -0.0169316 0.00866592"
mass="3.87494" diaginertia="0.0214195 0.0167127 0.0126452"/> <!--seems off-->
<joint name="wam/shoulder_pitch_joint_right" range="-2 2" damping="0.55"/>
<geom name="shoulder_pitch_link_fine" class="viz" mesh="shoulder_pitch_link_fine" rgba="1 1 1 0"/>
<geom name="shoulder_pitch_link_convex" class="col" mesh="shoulder_pitch_link_convex"/>
<body name="wam/upper_arm_link_right" pos="0 0 0" quat="0.707107 0.707107 0 0">
<inertial pos="0.00683259 3.309e-005 0.392492" quat="0.647136 0.0170822 0.0143038 0.762049"
mass="2.20228" diaginertia="0.0592718 0.0592207 0.00313419"/>
<joint name="wam/shoulder_yaw_joint_right" range="-2.8 2.8" damping="1.65"/>
<geom name="upper_arm_link_fine" class="viz" mesh="upper_arm_link_fine" rgba="1 1 1 0"/>
<geom name="upper_arm_link_convex_decomposition_p1" class="col"
mesh="upper_arm_link_convex_decomposition_p1" rgba="0.094 0.48 0.804 1"/>
<geom name="upper_arm_link_convex_decomposition_p2" class="col"
mesh="upper_arm_link_convex_decomposition_p2" rgba="0.094 0.48 0.804 1"/>
<body name="wam/forearm_link_right" pos="0.045 0 0.55" quat="0.707107 -0.707107 0 0">
<inertial pos="-0.0400149 -0.142717 -0.00022942"
quat="0.704281 0.706326 0.0180333 0.0690353" mass="0.500168"
diaginertia="0.0151047 0.0148285 0.00275805"/>
<joint name="wam/elbow_pitch_joint_right" range="-0.9 3.1" damping="0.88"/>
<geom name="elbow_link_fine" class="viz" mesh="elbow_link_fine" rgba="1 1 1 0"/>
<geom name="elbow_link_convex" class="col" mesh="elbow_link_convex"/>
<geom name="forearm_link_fine" class="viz" mesh="forearm_link_fine" pos="-.045 -0.0730 0"
euler="1.57 0 0" rgba="1 1 1 0"/>
<geom name="forearm_link_convex_decomposition_p1" class="col"
mesh="forearm_link_convex_decomposition_p1" pos="-0.045 -0.0730 0"
euler="1.57 0 0" rgba="0.094 0.48 0.804 1"/>
<geom name="forearm_link_convex_decomposition_p2" class="col"
mesh="forearm_link_convex_decomposition_p2" pos="-.045 -0.0730 0"
euler="1.57 0 0" rgba="0.094 0.48 0.804 1"/>
<body name="wam/wrist_yaw_link_right" pos="-0.045 -0.3 0" quat="0.707107 0.707107 0 0">
<inertial pos="8.921e-005 0.00435824 -0.00511217"
quat="0.630602 0.776093 0.00401969 -0.002372" mass="1.05376"
diaginertia="0.000555168 0.00046317 0.000234072"/> <!--this is an approximation-->
<joint name="wam/wrist_yaw_joint_right" range="-4.8 1.3" damping="0.55"/>
<geom name="wrist_yaw_link_fine" class="viz" mesh="wrist_yaw_link_fine" rgba="1 1 1 0"/>
<geom name="wrist_yaw_link_convex_decomposition_p1" class="col"
mesh="wrist_yaw_link_convex_decomposition_p1"/>
<geom name="wrist_yaw_link_convex_decomposition_p2" class="col"
mesh="wrist_yaw_link_convex_decomposition_p2"/>
<body name="wam/wrist_pitch_link_right" pos="0 0 0" quat="0.707107 -0.707107 0 0">
<inertial pos="-0.00012262 -0.0246834 -0.0170319"
quat="0.630602 0.776093 0.00401969 -0.002372" mass="0.517974"
diaginertia="0.000555168 0.00046317 0.000234072"/>
<joint name="wam/wrist_pitch_joint_right" range="-1.6 1.6" damping="0.11"/>
<geom name="wrist_pitch_link_fine" class="viz" mesh="wrist_pitch_link_fine"
rgba="1 1 1 0"/>
<geom name="wrist_pitch_link_convex_decomposition_p1" rgba="1 0.5 0.313 1"
class="col" mesh="wrist_pitch_link_convex_decomposition_p1"/>
<geom name="wrist_pitch_link_convex_decomposition_p2" rgba="1 0.5 0.313 1"
class="col" mesh="wrist_pitch_link_convex_decomposition_p2"/>
<geom name="wrist_pitch_link_convex_decomposition_p3" rgba="1 0.5 0.313 1"
class="col" mesh="wrist_pitch_link_convex_decomposition_p3"/>
<body name="wam/wrist_palm_link_right" pos="0 0 0" quat="0.707107 0.707107 0 0">
<inertial pos="0 0 0.055" quat="0.707107 0 0 0.707107" mass="0.0828613"
diaginertia="0.00020683 0.00010859 0.00010851"/>
<joint name="wam/palm_yaw_joint_right" range="-2.2 2.2" damping="0.11"/>
<geom name="wrist_palm_link_fine" class="viz" mesh="wrist_palm_link_fine"
rgba="1 1 1 0"/>
<geom name="wrist_palm_link_convex" class="col" mesh="wrist_palm_link_convex"/>
<!-- EE=wam/paddle, configure name to the end effector name-->
<body name="EE" pos="0 0 0.26" childclass="contact_geom">
<geom name="bat" type="cylinder" size="0.075 0.005" rgba="1 0 0 1"
quat="0.71 0 0.71 0"/>
<geom name="wam/paddle_handle" type="box" size="0.005 0.01 0.05" pos="0 0 -0.08"
rgba="1 1 1 1"/>
<!-- Extract information for sampling goals.-->
<site name="wam/paddle_center" pos="0 0 0" rgba="1 1 1 1" size="0.00001"/>
</body>
</body>
</body>
</body>
</body>
</body>
</body>
</body>
</body>
</mujocoinclue>

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@ -1,38 +0,0 @@
<mujocoinclude>
<body name="table_tennis_table" pos="0 0 0">
<geom class="contact_geom" name="table_base_1" type="box" size="0.05 0.05 .375" rgba="1 1 1 1"
pos="1 0.7 0.375"/>
<geom class="contact_geom" name="table_base_2" type="box" size="0.05 0.05 .375" rgba="1 1 1 1"
pos="1 -0.7 0.375"/>
<geom class="contact_geom" name="table_base_3" type="box" size="0.05 0.05 .375" rgba="1 1 1 1"
pos="-1 -0.7 0.375"/>
<geom class="contact_geom" name="table_base_4" type="box" size="0.05 0.05 .375" rgba="1 1 1 1"
pos="-1 0.7 0.375"/>
<body name="table_top" pos="0 0 0.76">
<geom class="contact_geom" name="table_tennis_table" type="box" size="1.37 .7625 .01" rgba="0 0 0.5 1"
pos="0 0 0"/>
<!-- <geom class="contact_geom" name="table_tennis_table_right_side" type="box" size="0.685 .7625 .01"-->
<!-- rgba="0.5 0 0 1" pos="0.685 0 0"/>-->
<!-- <geom class="contact_geom" name="table_tennis_table_left_side" type="box" size="0.685 .7625 .01"-->
<!-- rgba="0 0.5 0 1" pos="-0.685 0 0"/>-->
<site name="left_up_corner" pos="-1.37 .7625 0.01" rgba="1 1 1 1" size="0.00001"/>
<site name="middle_up_corner" pos="0 .7625 0.01" rgba="1 1 1 1" size="0.00001"/>
<site name="left_down_corner" pos="-1.37 -0.7625 0.01" rgba="1 1 1 1" size="0.00001"/>
<site name="middle_down_corner" pos="0 -.7625 0.01" rgba="1 1 1 1" size="0.00001"/>
<geom class="contact_geom" name="table_tennis_net" type="box" size="0.01 0.915 0.07625"
material="floor_plane"
rgba="0 0 1 0.5"
pos="0 0 0.08625"/>
<geom class="contact_geom" name="left_while_line" type="box" size="1.37 .02 .001" rgba="1 1 1 1"
pos="0 -0.7425 0.01"/>
<geom class="contact_geom" name="center_while_line" type="box" size="1.37 .01 .001" rgba="1 1 1 1"
pos="0 0 0.01"/>
<geom class="contact_geom" name="right_while_line" type="box" size="1.37 .02 .001" rgba="1 1 1 1"
pos="0 0.7425 0.01"/>
<geom class="contact_geom" name="right_side_line" type="box" size="0.02 .7625 .001" rgba="1 1 1 1"
pos="1.35 0 0.01"/>
<geom class="contact_geom" name="left_side_line" type="box" size="0.02 .7625 .001" rgba="1 1 1 1"
pos="-1.35 0 0.01"/>
</body>
</body>
</mujocoinclude>

View File

@ -1,10 +0,0 @@
<mujocoinclude>
<body name="target_ball" pos="-1.2 -0.6 1.5">
<joint axis="1 0 0" damping="0.0" name="tar:x" pos="0 0 0" stiffness="0" type="slide" frictionloss="0"/>
<joint axis="0 1 0" damping="0.0" name="tar:y" pos="0 0 0" stiffness="0" type="slide" frictionloss="0"/>
<joint axis="0 0 1" damping="0.0" name="tar:z" pos="0 0 0" stiffness="0" type="slide" frictionloss="0"/>
<geom size="0.025 0.025 0.025" type="sphere" condim="4" name="target_ball" rgba="1 1 0 1" mass="0.1"
friction="0.1 0.1 0.1" solimp="1 1 0" solref="0.1 0.03"/>
<site name="target_ball" pos="0 0 0" size="0.02 0.02 0.02" rgba="1 0 0 1" type="sphere"/>
</body>
</mujocoinclude>

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@ -1,80 +0,0 @@
<mujocoinclude>
<body name="test_ball_table" pos="1 0 4">
<joint axis="1 0 0" damping="0.0" name="tar:x_test_ball_table" pos="0 0 0" stiffness="0" type="slide"
frictionloss="0"/>
<joint axis="0 1 0" damping="0.0" name="tar:y_test_ball_table" pos="0 0 0" stiffness="0" type="slide"
frictionloss="0"/>
<joint axis="0 0 1" damping="0.0" name="tar:z_test_ball_table" pos="0 0 0" stiffness="0" type="slide"
frictionloss="0"/>
<geom size="0.025 0.025 0.025" type="sphere" condim="4" name="test_ball_table" rgba="0 1 0 1" mass="0.1"
friction="0.1 0.1 0.1" solimp="1 1 0" solref="0.1 0.03"/>
<site name="test_ball_table" pos="0 0 0" size="0.02 0.02 0.02" rgba="0 1 0 1" type="sphere"/>
</body>
<body name="test_ball_net" pos="0 0 4">
<joint axis="1 0 0" damping="0.0" name="tar:x_test_ball_net" pos="0 0 0" stiffness="0" type="slide"
frictionloss="0"/>
<joint axis="0 1 0" damping="0.0" name="tar:y_test_ball_net" pos="0 0 0" stiffness="0" type="slide"
frictionloss="0"/>
<joint axis="0 0 1" damping="0.0" name="tar:z_test_ball_net" pos="0 0 0" stiffness="0" type="slide"
frictionloss="0"/>
<geom size="0.025 0.025 0.025" type="sphere" condim="4" name="test_ball_net" rgba="1 1 0 1" mass="0.1"
friction="0.1 0.1 0.1" solimp="1 1 0" solref="0.1 0.03"/>
<site name="test_ball_net" pos="0 0 0" size="0.02 0.02 0.02" rgba="0 1 0 1" type="sphere"/>
</body>
<body name="test_ball_racket_0" pos="2.54919187 0.81642672 4">
<joint axis="1 0 0" damping="0.0" name="tar:x_test_ball_racket_0" pos="0 0 0" stiffness="0" type="slide"
frictionloss="0"/>
<joint axis="0 1 0" damping="0.0" name="tar:y_test_ball_racket_0" pos="0 0 0" stiffness="0" type="slide"
frictionloss="0"/>
<joint axis="0 0 1" damping="0.0" name="tar:z_test_ball_racket_0" pos="0 0 0" stiffness="0" type="slide"
frictionloss="0"/>
<geom size="0.025 0.025 0.025" type="sphere" condim="4" name="test_ball_racket_0" rgba="1 0 1 1" mass="0.1"
friction="0.1 0.1 0.1" solimp="1 1 0" solref="0.1 0.03"/>
<site name="test_ball_racket_0" pos="0 0 0" size="0.02 0.02 0.02" rgba="0 1 0 1" type="sphere"/>
</body>
<body name="test_ball_racket_1" pos="2.54919187 0.81642672 4.5">
<joint axis="1 0 0" damping="0.0" name="tar:x_test_ball_racket_1" pos="0 0 0" stiffness="0" type="slide"
frictionloss="0"/>
<joint axis="0 1 0" damping="0.0" name="tar:y_test_ball_racket_1" pos="0 0 0" stiffness="0" type="slide"
frictionloss="0"/>
<joint axis="0 0 1" damping="0.0" name="tar:z_test_ball_racket_1" pos="0 0 0" stiffness="0" type="slide"
frictionloss="0"/>
<geom size="0.025 0.025 0.025" type="sphere" condim="4" name="test_ball_racket_1" rgba="1 0 1 1" mass="0.1"
friction="0.1 0.1 0.1" solimp="1 1 0" solref="0.1 0.03"/>
<site name="test_ball_racket_1" pos="0 0 0" size="0.02 0.02 0.02" rgba="0 1 0 1" type="sphere"/>
</body>
<body name="test_ball_racket_2" pos="2.54919187 0.81642672 3">
<joint axis="1 0 0" damping="0.0" name="tar:x_test_ball_racket_2" pos="0 0 0" stiffness="0" type="slide"
frictionloss="0"/>
<joint axis="0 1 0" damping="0.0" name="tar:y_test_ball_racket_2" pos="0 0 0" stiffness="0" type="slide"
frictionloss="0"/>
<joint axis="0 0 1" damping="0.0" name="tar:z_test_ball_racket_2" pos="0 0 0" stiffness="0" type="slide"
frictionloss="0"/>
<geom size="0.025 0.025 0.025" type="sphere" condim="4" name="test_ball_racket_2" rgba="1 0 1 1" mass="0.1"
friction="0.1 0.1 0.1" solimp="1 1 0" solref="0.1 0.03"/>
<site name="test_ball_racket" pos="0 0 0" size="0.02 0.02 0.02" rgba="0 1 0 1" type="sphere"/>
</body>
<body name="test_ball_racket_3" pos="2.54919187 0.81642672 10">
<joint axis="1 0 0" damping="0.0" name="tar:x_test_ball_racket_3" pos="0 0 0" stiffness="0" type="slide"
frictionloss="0"/>
<joint axis="0 1 0" damping="0.0" name="tar:y_test_ball_racket_3" pos="0 0 0" stiffness="0" type="slide"
frictionloss="0"/>
<joint axis="0 0 1" damping="0.0" name="tar:z_test_ball_racket_3" pos="0 0 0" stiffness="0" type="slide"
frictionloss="0"/>
<geom size="0.025 0.025 0.025" type="sphere" condim="4" name="test_ball_racket_3" rgba="1 0 1 1" mass="0.1"
friction="0.1 0.1 0.1" solimp="1 1 0" solref="0.1 0.03"/>
<site name="test_ball_racket_3" pos="0 0 0" size="0.02 0.02 0.02" rgba="0 1 0 1" type="sphere"/>
</body>
<!-- <body name="test_ball_racket_4" pos="2.54919187 0.81642672 4">-->
<!-- <joint axis="1 0 0" damping="0.0" name="tar:x_test_ball_racket_4" pos="0 0 0" stiffness="0" type="slide"-->
<!-- frictionloss="0"/>-->
<!-- <joint axis="0 1 0" damping="0.0" name="tar:y_test_ball_racket_4" pos="0 0 0" stiffness="0" type="slide"-->
<!-- frictionloss="0"/>-->
<!-- <joint axis="0 0 1" damping="0.0" name="tar:z_test_ball_racket_4" pos="0 0 0" stiffness="0" type="slide"-->
<!-- frictionloss="0"/>-->
<!-- <geom size="0.025 0.025 0.025" type="sphere" condim="4" name="test_ball_racket_4" rgba="1 0 0 1" mass="0.1"-->
<!-- friction="0.1 0.1 0.1" solimp="1 1 0" solref="0.1 0.03"/>-->
<!-- <site name="test_ball_racket_4" pos="0 0 0" size="0.02 0.02 0.02" rgba="0 1 0 1" type="sphere"/>-->
<!-- </body>-->
</mujocoinclude>

View File

@ -1,19 +0,0 @@
<mujocoinclude>
<actuator>
<!-- <position ctrlrange="-2.6 2.6" joint="wam/base_yaw_joint_right" kp="100.0" />-->
<!-- <position ctrlrange="-1.985 1.985" joint="wam/shoulder_pitch_joint_right" kp="162.0" />-->
<!-- <position ctrlrange="-2.8 2.8" joint="wam/shoulder_yaw_joint_right" kp="100.0" />-->
<!-- <position ctrlrange="-0.9 3.14159" joint="wam/elbow_pitch_joint_right" kp="122.0" />-->
<!-- <position ctrlrange="-4.55 1.25" joint="wam/wrist_yaw_joint_right" kp="100.0" />-->
<!-- <position ctrlrange="-1.5707 1.5707" joint="wam/wrist_pitch_joint_right" kp="102.0" />-->
<!-- <position ctrlrange="-3 3" joint="wam/palm_yaw_joint_right" kp="100.0" />-->
<position ctrlrange="-2.6 2.6" joint="wam/base_yaw_joint_right" kp="151.0"/>
<position ctrlrange="-1.985 1.985" joint="wam/shoulder_pitch_joint_right" kp="125.0"/>
<position ctrlrange="-2.8 2.8" joint="wam/shoulder_yaw_joint_right" kp="122.0"/>
<position ctrlrange="-0.9 3.14159" joint="wam/elbow_pitch_joint_right" kp="121.0"/>
<position ctrlrange="-4.55 1.25" joint="wam/wrist_yaw_joint_right" kp="99.0"/>
<position ctrlrange="-1.5707 1.5707" joint="wam/wrist_pitch_joint_right" kp="103.0"/>
<position ctrlrange="-3 3" joint="wam/palm_yaw_joint_right" kp="99.0"/>
</actuator>
</mujocoinclude>

View File

@ -1,49 +0,0 @@
<mujocoinclude>
<default>
<default class="wam">
<joint type="hinge" limited="true" pos="0 0 0" axis="0 0 1"/>
</default>
<default class="viz">
<geom type="mesh" contype="0" conaffinity="0" group="1" rgba="1 1 1 1"/>
</default>
<default class="col">
<geom type="mesh" contype="0" conaffinity="1" group="0" rgba="1 1 1 1"/>
</default>
<default class="contact_geom">
<geom condim="4" friction="0.1 0.1 0.1" margin="0" solimp="1 1 0" solref="0.1 0.03"/>
<!-- <geom condim="4" friction="0 0 0" margin="0" solimp="1 1 0" solref="0.01 1.1"/>-->
</default>
</default>
<asset>
<mesh file="base_link_fine.stl"/>
<mesh file="base_link_convex.stl"/>
<mesh file="shoulder_link_fine.stl"/>
<mesh file="shoulder_link_convex_decomposition_p1.stl"/>
<mesh file="shoulder_link_convex_decomposition_p2.stl"/>
<mesh file="shoulder_link_convex_decomposition_p3.stl"/>
<mesh file="shoulder_pitch_link_fine.stl"/>
<mesh file="shoulder_pitch_link_convex.stl"/>
<mesh file="upper_arm_link_fine.stl"/>
<mesh file="upper_arm_link_convex_decomposition_p1.stl"/>
<mesh file="upper_arm_link_convex_decomposition_p2.stl"/>
<mesh file="elbow_link_fine.stl"/>
<mesh file="elbow_link_convex.stl"/>
<mesh file="forearm_link_fine.stl"/>
<mesh file="forearm_link_convex_decomposition_p1.stl"/>
<mesh file="forearm_link_convex_decomposition_p2.stl"/>
<mesh file="wrist_yaw_link_fine.stl"/>
<mesh file="wrist_yaw_link_convex_decomposition_p1.stl"/>
<mesh file="wrist_yaw_link_convex_decomposition_p2.stl"/>
<mesh file="wrist_pitch_link_fine.stl"/>
<mesh file="wrist_pitch_link_convex_decomposition_p1.stl"/>
<mesh file="wrist_pitch_link_convex_decomposition_p2.stl"/>
<mesh file="wrist_pitch_link_convex_decomposition_p3.stl"/>
<mesh file="wrist_palm_link_fine.stl"/>
<mesh file="wrist_palm_link_convex.stl"/>
<texture builtin="checker" height="512" name="texplane" rgb1=".2 .3 .4" rgb2=".1 0.15 0.2" type="2d"
width="512"/>
<material name="floor_plane" reflectance="0.5" texrepeat="1 1" texture="texplane" texuniform="true"/>
</asset>
</mujocoinclude>

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@ -1,41 +0,0 @@
<mujoco model="table_tennis(v0.1)">
<compiler angle="radian" coordinate="local" meshdir="meshes/" />
<option gravity="0 0 -9.81" timestep="0.002">
<flag warmstart="enable" />
</option>
<custom>
<numeric data="0 0 0 0 0 0 0" name="START_ANGLES" />
</custom>
<include file="shared.xml" />
<worldbody>
<light cutoff="60" diffuse="1 1 1" dir="-.1 -.2 -1.3" directional="true" exponent="1" pos=".1 .2 1.3" specular=".1 .1 .1" />
<geom conaffinity="1" contype="1" material="floor_plane" name="floor" pos="0 0 0" size="10 5 1" type="plane" />
<include file="include_table.xml" />
<include file="include_barrett_wam_7dof_right.xml" />
<include file="include_target_ball.xml" />
</worldbody>
<include file="right_arm_actuator.xml" />
</mujoco>

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@ -1,244 +0,0 @@
import numpy as np
from gym import spaces
from gym.envs.robotics import robot_env, utils
# import xml.etree.ElementTree as ET
from alr_envs.alr.mujoco.gym_table_tennis.utils.rewards.hierarchical_reward import HierarchicalRewardTableTennis
import glfw
from alr_envs.alr.mujoco.gym_table_tennis.utils.experiment import ball_initialize
from pathlib import Path
import os
class TableTennisEnv(robot_env.RobotEnv):
"""Class for Table Tennis environment.
"""
def __init__(self, n_substeps=1,
model_path=None,
initial_qpos=None,
initial_ball_state=None,
config=None,
reward_obj=None
):
"""Initializes a new mujoco based Table Tennis environment.
Args:
model_path (string): path to the environments XML file
initial_qpos (dict): a dictionary of joint names and values that define the initial
n_actions: Number of joints
n_substeps (int): number of substeps the simulation runs on every call to step
scale (double): limit maximum change in position
initial_ball_state: to reset the ball state
"""
# self.config = config.config
if model_path is None:
path_cws = Path.cwd()
print(path_cws)
current_dir = Path(os.path.split(os.path.realpath(__file__))[0])
table_tennis_env_xml_path = current_dir / "assets"/"table_tennis_env.xml"
model_path = str(table_tennis_env_xml_path)
self.config = config
action_space = True # self.config['trajectory']['args']['action_space']
time_step = 0.002 # self.config['mujoco_sim_env']['args']["time_step"]
if initial_qpos is None:
initial_qpos = {"wam/base_yaw_joint_right": 1.5,
"wam/shoulder_pitch_joint_right": 1,
"wam/shoulder_yaw_joint_right": 0,
"wam/elbow_pitch_joint_right": 1,
"wam/wrist_yaw_joint_right": 1,
"wam/wrist_pitch_joint_right": 0,
"wam/palm_yaw_joint_right": 0}
# initial_qpos = [1.5, 1, 0, 1, 1, 0, 0] # self.config['robot_config']['args']['initial_qpos']
# TODO should read all configuration in config
assert initial_qpos is not None, "Must initialize the initial q position of robot arm"
n_actions = 7
self.initial_qpos_value = np.array(list(initial_qpos.values())).copy()
# self.initial_qpos_value = np.array(initial_qpos)
# # change time step in .xml file
# tree = ET.parse(model_path)
# root = tree.getroot()
# for option in root.findall('option'):
# option.set("timestep", str(time_step))
#
# tree.write(model_path)
super(TableTennisEnv, self).__init__(
model_path=model_path, n_substeps=n_substeps, n_actions=n_actions,
initial_qpos=initial_qpos)
if action_space:
self.action_space = spaces.Box(low=np.array([-2.6, -2.0, -2.8, -0.9, -4.8, -1.6, -2.2]),
high=np.array([2.6, 2.0, 2.8, 3.1, 1.3, 1.6, 2.2]),
dtype='float64')
else:
self.action_space = spaces.Box(low=np.array([-np.inf] * 7),
high=np.array([-np.inf] * 7),
dtype='float64')
self.scale = None
self.desired_pos = None
self.n_actions = n_actions
self.action = None
self.time_step = time_step
self._dt = time_step
self.paddle_center_pos = self.sim.data.get_site_xpos('wam/paddle_center')
if reward_obj is None:
self.reward_obj = HierarchicalRewardTableTennis()
else:
self.reward_obj = reward_obj
if initial_ball_state is not None:
self.initial_ball_state = initial_ball_state
else:
self.initial_ball_state = ball_initialize(random=False)
self.target_ball_pos = self.sim.data.get_site_xpos("target_ball")
self.racket_center_pos = self.sim.data.get_site_xpos("wam/paddle_center")
def close(self):
if self.viewer is not None:
glfw.destroy_window(self.viewer.window)
# self.viewer.window.close()
self.viewer = None
self._viewers = {}
# GoalEnv methods
# ----------------------------
def compute_reward(self, achieved_goal, goal, info):
# reset the reward, if action valid
# right_court_contact_obj = ["target_ball", "table_tennis_table_right_side"]
# right_court_contact_detector = self.reward_obj.contact_detection(self, right_court_contact_obj)
# if right_court_contact_detector:
# print("can detect the table ball contact")
self.reward_obj.total_reward = 0
# Stage 1 Hitting
self.reward_obj.hitting(self)
# if not hitted, return the highest reward
if not self.reward_obj.goal_achievement:
# return self.reward_obj.highest_reward
return self.reward_obj.total_reward
# # Stage 2 Right Table Contact
# self.reward_obj.right_table_contact(self)
# if not self.reward_obj.goal_achievement:
# return self.reward_obj.highest_reward
# # Stage 2 Net Contact
# self.reward_obj.net_contact(self)
# if not self.reward_obj.goal_achievement:
# return self.reward_obj.highest_reward
# Stage 3 Opponent court Contact
# self.reward_obj.landing_on_opponent_court(self)
# if not self.reward_obj.goal_achievement:
# print("self.reward_obj.highest_reward: ", self.reward_obj.highest_reward)
# TODO
self.reward_obj.target_achievement(self)
# return self.reward_obj.highest_reward
return self.reward_obj.total_reward
def _reset_sim(self):
self.sim.set_state(self.initial_state)
[initial_x, initial_y, initial_z, v_x, v_y, v_z] = self.initial_ball_state
self.sim.data.set_joint_qpos('tar:x', initial_x)
self.sim.data.set_joint_qpos('tar:y', initial_y)
self.sim.data.set_joint_qpos('tar:z', initial_z)
self.energy_corrected = True
self.give_reflection_reward = False
# velocity is positive direction
self.sim.data.set_joint_qvel('tar:x', v_x)
self.sim.data.set_joint_qvel('tar:y', v_y)
self.sim.data.set_joint_qvel('tar:z', v_z)
# Apply gravity compensation
if self.sim.data.qfrc_applied[:7] is not self.sim.data.qfrc_bias[:7]:
self.sim.data.qfrc_applied[:7] = self.sim.data.qfrc_bias[:7]
self.sim.forward()
return True
def _env_setup(self, initial_qpos):
for name, value in initial_qpos.items():
self.sim.data.set_joint_qpos(name, value)
# Apply gravity compensation
if self.sim.data.qfrc_applied[:7] is not self.sim.data.qfrc_bias[:7]:
self.sim.data.qfrc_applied[:7] = self.sim.data.qfrc_bias[:7]
self.sim.forward()
# Get the target position
self.initial_paddle_center_xpos = self.sim.data.get_site_xpos('wam/paddle_center').copy()
self.initial_paddle_center_vel = None # self.sim.get_site_
def _sample_goal(self):
goal = self.initial_paddle_center_xpos[:3] + self.np_random.uniform(-0.2, 0.2, size=3)
return goal.copy()
def _get_obs(self):
# positions of racket center
paddle_center_pos = self.sim.data.get_site_xpos('wam/paddle_center')
ball_pos = self.sim.data.get_site_xpos("target_ball")
dt = self.sim.nsubsteps * self.sim.model.opt.timestep
paddle_center_velp = self.sim.data.get_site_xvelp('wam/paddle_center') * dt
robot_qpos, robot_qvel = utils.robot_get_obs(self.sim)
wrist_state = robot_qpos[-3:]
wrist_vel = robot_qvel[-3:] * dt # change to a scalar if the gripper is made symmetric
# achieved_goal = paddle_body_EE_pos
obs = np.concatenate([
paddle_center_pos, paddle_center_velp, wrist_state, wrist_vel
])
out_dict = {
'observation': obs.copy(),
'achieved_goal': paddle_center_pos.copy(),
'desired_goal': self.goal.copy(),
'q_pos': self.sim.data.qpos[:].copy(),
"ball_pos": ball_pos.copy(),
# "hitting_flag": self.reward_obj.hitting_flag
}
return out_dict
def _step_callback(self):
pass
def _set_action(self, action):
# Apply gravity compensation
if self.sim.data.qfrc_applied[:7] is not self.sim.data.qfrc_bias[:7]:
self.sim.data.qfrc_applied[:7] = self.sim.data.qfrc_bias[:7]
# print("set action process running")
assert action.shape == (self.n_actions,)
self.action = action.copy() # ensure that we don't change the action outside of this scope
pos_ctrl = self.action[:] # limit maximum change in position
pos_ctrl = np.clip(pos_ctrl, self.action_space.low, self.action_space.high)
# get desired trajectory
self.sim.data.qpos[:7] = pos_ctrl
self.sim.forward()
self.desired_pos = self.sim.data.get_site_xpos('wam/paddle_center').copy()
self.sim.data.ctrl[:] = pos_ctrl
def _is_success(self, achieved_goal, desired_goal):
pass
if __name__ == '__main__':
render_mode = "human" # "human" or "partial" or "final"
env = TableTennisEnv()
env.reset()
# env.render(mode=render_mode)
for i in range(500):
# objective.load_result("/tmp/cma")
# test with random actions
ac = env.action_space.sample()
# ac[0] += np.pi/2
obs, rew, d, info = env.step(ac)
env.render(mode=render_mode)
print(rew)
if d:
break
env.close()

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import numpy as np
from gym.utils import seeding
from alr_envs.alr.mujoco.gym_table_tennis.utils.util import read_yaml, read_json
from pathlib import Path
def ball_initialize(random=False, scale=False, context_range=None, scale_value=None):
if random:
if scale:
# if scale_value is None:
scale_value = context_scale_initialize(context_range)
v_x, v_y, v_z = [2.5, 2, 0.5] * scale_value
dx = 1
dy = 0
dz = 0.05
else:
seed = None
np_random, seed = seeding.np_random(seed)
dx = np_random.uniform(-0.1, 0.1)
dy = np_random.uniform(-0.1, 0.1)
dz = np_random.uniform(-0.1, 0.1)
v_x = np_random.uniform(1.7, 1.8)
v_y = np_random.uniform(0.7, 0.8)
v_z = np_random.uniform(0.1, 0.2)
# print(dx, dy, dz, v_x, v_y, v_z)
# else:
# dx = -0.1
# dy = 0.05
# dz = 0.05
# v_x = 1.5
# v_y = 0.7
# v_z = 0.06
# initial_x = -0.6 + dx
# initial_y = -0.3 + dy
# initial_z = 0.8 + dz
else:
if scale:
v_x, v_y, v_z = [2.5, 2, 0.5] * scale_value
else:
v_x = 2.5
v_y = 2
v_z = 0.5
dx = 1
dy = 0
dz = 0.05
initial_x = 0 + dx
initial_y = -0.2 + dy
initial_z = 0.3 + dz
# print("initial ball state: ", initial_x, initial_y, initial_z, v_x, v_y, v_z)
initial_ball_state = np.array([initial_x, initial_y, initial_z, v_x, v_y, v_z])
return initial_ball_state
def context_scale_initialize(range):
"""
Returns:
"""
low, high = range
scale = np.random.uniform(low, high, 1)
return scale
def config_handle_generation(config_file_path):
"""Generate config handle for multiprocessing
Args:
config_file_path:
Returns:
"""
cfg_fname = Path(config_file_path)
# .json and .yml file
if cfg_fname.suffix == ".json":
config = read_json(cfg_fname)
elif cfg_fname.suffix == ".yml":
config = read_yaml(cfg_fname)
return config

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@ -1,402 +0,0 @@
import numpy as np
import logging
class HierarchicalRewardTableTennis(object):
"""Class for hierarchical reward function for table tennis experiment.
Return Highest Reward.
Reward = 0
Step 1: Action Valid. Upper Bound 0
[-, 0]
Reward += -1 * |hit_duration - hit_duration_threshold| * |hit_duration < hit_duration_threshold| * 10
Step 2: Hitting. Upper Bound 2
if hitting:
[0, 2]
Reward = 2 * (1 - tanh(|shortest_hitting_dist|))
if not hitting:
[0, 0.2]
Reward = 2 * (1 - tanh(|shortest_hitting_dist|))
Step 3: Target Point Achievement. Upper Bound 6
[0, 4]
if table_contact_detector:
Reward += 1
Reward += (1 - tanh(|shortest_hitting_dist|)) * 2
if contact_coordinate[0] < 0:
Reward += 1
else:
Reward += 0
elif:
Reward += (1 - tanh(|shortest_hitting_dist|))
"""
def __init__(self):
self.reward = None
self.goal_achievement = False
self.total_reward = 0
self.shortest_hitting_dist = 1000
self.highest_reward = -1000
self.lowest_corner_dist = 100
self.right_court_contact_detector = False
self.table_contact_detector = False
self.floor_contact_detector = False
self.radius = 0.025
self.min_ball_x_pos = 100
self.hit_contact_detector = False
self.net_contact_detector = False
self.ratio = 1
self.lowest_z = 100
self.target_flag = False
self.dist_target_virtual = 100
self.ball_z_pos_lowest = 100
self.hitting_flag = False
self.hitting_time_point = None
self.ctxt_dim = None
self.context_range_bounds = None
# self.ctxt_out_of_range_punishment = None
# self.ctxt_in_side_of_range_punishment = None
#
# def check_where_invalid(self, ctxt, context_range_bounds, set_to_valid_region=False):
# idx_max = []
# idx_min = []
# for dim in range(self.ctxt_dim):
# min_dim = context_range_bounds[0][dim]
# max_dim = context_range_bounds[1][dim]
# idx_max_c = np.where(ctxt[:, dim] > max_dim)[0]
# idx_min_c = np.where(ctxt[:, dim] < min_dim)[0]
# if set_to_valid_region:
# if idx_max_c.shape[0] != 0:
# ctxt[idx_max_c, dim] = max_dim
# if idx_min_c.shape[0] != 0:
# ctxt[idx_min_c, dim] = min_dim
# idx_max.append(idx_max_c)
# idx_min.append(idx_min_c)
# return idx_max, idx_min, ctxt
def check_valid(self, scale, context_range_bounds):
min_dim = context_range_bounds[0][0]
max_dim = context_range_bounds[1][0]
valid = (scale < max_dim) and (scale > min_dim)
return valid
@classmethod
def goal_distance(cls, goal_a, goal_b):
assert goal_a.shape == goal_b.shape
return np.linalg.norm(goal_a - goal_b, axis=-1)
def refresh_highest_reward(self):
if self.total_reward >= self.highest_reward:
self.highest_reward = self.total_reward
def duration_valid(self):
pass
def huge_value_unstable(self):
self.total_reward += -10
self.highest_reward = -1
def context_valid(self, context):
valid = self.check_valid(context.copy(), context_range_bounds=self.context_range_bounds)
# when using dirac punishments
if valid:
self.total_reward += 1 # If Action Valid and Context Valid, total_reward = 0
else:
self.total_reward += 0
self.refresh_highest_reward()
# If in the ctxt, add 1, otherwise, 0
def action_valid(self, durations=None):
"""Ensure the execution of the robot movement with parameters which are in a valid domain.
Time should always be positive,
the joint position of the robot should be a subset of [π, π].
if all parameters are valid, the robot gets a zero score,
otherwise it gets a negative score proportional to how much it is beyond the valid parameter domain.
Returns:
rewards: if valid, reward is equal to 0.
if not valid, reward is negative and proportional to the distance beyond the valid parameter domain
"""
assert durations.shape[0] == 2, "durations type should be np.array and the shape should be 2"
# pre_duration = durations[0]
hit_duration = durations[1]
# pre_duration_thres = 0.01
hit_duration_thres = 1
# self.goal_achievement = np.all(
# [(pre_duration > pre_duration_thres), (hit_duration > hit_duration_thres), (0.3 < pre_duration < 0.6)])
self.goal_achievement = (hit_duration > hit_duration_thres)
if self.goal_achievement:
self.total_reward = -1
self.goal_achievement = True
else:
# self.total_reward += -1 * ((np.abs(pre_duration - pre_duration_thres) * int(
# pre_duration < pre_duration_thres) + np.abs(hit_duration - hit_duration_thres) * int(
# hit_duration < hit_duration_thres)) * 10)
self.total_reward = -1 * ((np.abs(hit_duration - hit_duration_thres) * int(
hit_duration < hit_duration_thres)) * 10)
self.total_reward += -1
self.goal_achievement = False
self.refresh_highest_reward()
def motion_penalty(self, action, high_motion_penalty):
"""Protects the robot from high acceleration and dangerous movement.
"""
if not high_motion_penalty:
reward_ctrl = - 0.05 * np.square(action).sum()
else:
reward_ctrl = - 0.075 * np.square(action).sum()
self.total_reward += reward_ctrl
self.refresh_highest_reward()
self.goal_achievement = True
def hitting(self, env): # , target_ball_pos, racket_center_pos, hit_contact_detector=False
"""Hitting reward calculation
If racket successfully hit the ball, the reward +1
Otherwise calculate the distance between the center of racket and the center of ball,
reward = tanh(r/dist) if dist<1 reward almost 2 , if dist >= 1 reward is between [0, 0.2]
Args:
env:
Returns:
"""
hit_contact_obj = ["target_ball", "bat"]
target_ball_pos = env.target_ball_pos
racket_center_pos = env.racket_center_pos
# hit contact detection
# Record the hitting history
self.hitting_flag = False
if not self.hit_contact_detector:
self.hit_contact_detector = self.contact_detection(env, hit_contact_obj)
if self.hit_contact_detector:
print("First time detect hitting")
self.hitting_flag = True
if self.hit_contact_detector:
# TODO
dist = self.goal_distance(target_ball_pos, racket_center_pos)
if dist < 0:
dist = 0
# print("goal distance is:", dist)
if dist <= self.shortest_hitting_dist:
self.shortest_hitting_dist = dist
# print("shortest_hitting_dist is:", self.shortest_hitting_dist)
# Keep the shortest hitting distance.
dist_reward = 2 * (1 - np.tanh(np.abs(self.shortest_hitting_dist)))
# TODO sparse
# dist_reward = 2
self.total_reward += dist_reward
self.goal_achievement = True
# if self.hitting_time_point is not None and self.hitting_time_point > 600:
# self.total_reward += 1
else:
dist = self.goal_distance(target_ball_pos, racket_center_pos)
if dist <= self.shortest_hitting_dist:
self.shortest_hitting_dist = dist
dist_reward = 1 - np.tanh(self.shortest_hitting_dist)
reward = 0.2 * dist_reward # because it does not hit the ball, so multiply 0.2
self.total_reward += reward
self.goal_achievement = False
self.refresh_highest_reward()
@classmethod
def relu(cls, x):
return np.maximum(0, x)
# def right_table_contact(self, env):
# right_court_contact_obj = ["target_ball", "table_tennis_table_right_side"]
# if env.target_ball_pos[0] >= 0 and env.target_ball_pos[2] >= 0.7:
# # update right court contact detection
# if not self.right_court_contact_detector:
# self.right_court_contact_detector = self.contact_detection(env, right_court_contact_obj)
# if self.right_court_contact_detector:
# self.contact_x_pos = env.target_ball_pos[0]
# if self.right_court_contact_detector:
# self.total_reward += 1 - norm(0.685, 1).pdf(self.contact_x_pos) # x axis middle of right table
# self.goal_achievement = False
# else:
# self.total_reward += 1
# self.goal_achievement = True
# # else:
# # self.total_reward += 0
# # self.goal_achievement = False
# self.refresh_highest_reward()
# def net_contact(self, env):
# net_contact_obj = ["target_ball", "table_tennis_net"]
# # net_contact_detector = self.contact_detection(env, net_contact_obj)
# # ball_x_pos = env.target_ball_pos[0]
# # if self.min_ball_x_pos >= ball_x_pos:
# # self.min_ball_x_pos = ball_x_pos
# # table_left_edge_x_pos = -1.37
# # if np.abs(ball_x_pos) <= 0.01: # x threshold of net
# # if self.lowest_z >= env.target_ball_pos[2]:
# # self.lowest_z = env.target_ball_pos[2]
# # # construct a gaussian distribution of z
# # z_reward = 4 - norm(0, 0.1).pdf(self.lowest_z - 0.07625) # maximum 4
# # self.total_reward += z_reward
# # self.total_reward += 2 - np.minimum(1, self.relu(np.abs(self.min_ball_x_pos)))
# if not self.net_contact_detector:
# self.net_contact_detector = self.contact_detection(env, net_contact_obj)
# if self.net_contact_detector:
# self.total_reward += 0 # very high cost
# self.goal_achievement = False
# else:
# self.total_reward += 1
# self.goal_achievement = True
# self.refresh_highest_reward()
# def landing_on_opponent_court(self, env):
# # Very sparse reward
# # don't contact the right side court
# # right_court_contact_obj = ["target_ball", "table_tennis_table_right_side"]
# # right_court_contact_detector = self.contact_detection(env, right_court_contact_obj)
# left_court_contact_obj = ["target_ball", "table_tennis_table_left_side"]
# # left_court_contact_detector = self.contact_detection(env, left_court_contact_obj)
# # record the contact history
# # if not self.right_court_contact_detector:
# # self.right_court_contact_detector = self.contact_detection(env, right_court_contact_obj)
# if not self.table_contact_detector:
# self.table_contact_detector = self.contact_detection(env, left_court_contact_obj)
#
# dist_left_up_corner = self.goal_distance(env.target_ball_pos, env.sim.data.get_site_xpos("left_up_corner"))
# dist_middle_up_corner = self.goal_distance(env.target_ball_pos, env.sim.data.get_site_xpos("middle_up_corner"))
# dist_left_down_corner = self.goal_distance(env.target_ball_pos, env.sim.data.get_site_xpos("left_down_corner"))
# dist_middle_down_corner = self.goal_distance(env.target_ball_pos,
# env.sim.data.get_site_xpos("middle_down_corner"))
# dist_array = np.array(
# [dist_left_up_corner, dist_middle_up_corner, dist_left_down_corner, dist_middle_down_corner])
# dist_corner = np.amin(dist_array)
# if self.lowest_corner_dist >= dist_corner:
# self.lowest_corner_dist = dist_corner
#
# right_contact_cost = 1
# left_contact_reward = 2
# dist_left_table_reward = (2 - np.tanh(self.lowest_corner_dist))
# # TODO Try multi dimensional gaussian distribution
# # contact only the left side court
# if self.right_court_contact_detector:
# self.total_reward += 0
# self.goal_achievement = False
# if self.table_contact_detector:
# self.total_reward += left_contact_reward
# self.goal_achievement = False
# else:
# self.total_reward += dist_left_table_reward
# self.goal_achievement = False
# else:
# self.total_reward += right_contact_cost
# if self.table_contact_detector:
# self.total_reward += left_contact_reward
# self.goal_achievement = True
# else:
# self.total_reward += dist_left_table_reward
# self.goal_achievement = False
# self.refresh_highest_reward()
# # if self.left_court_contact_detector and not self.right_court_contact_detector:
# # self.total_reward += self.ratio * left_contact_reward
# # print("only left court reward return!!!!!!!!!")
# # print("contact only left court!!!!!!")
# # self.goal_achievement = True
# # # no contact with table
# # elif not self.right_court_contact_detector and not self.left_court_contact_detector:
# # self.total_reward += 0 + self.ratio * dist_left_table_reward
# # self.goal_achievement = False
# # # contact both side
# # elif self.right_court_contact_detector and self.left_court_contact_detector:
# # self.total_reward += self.ratio * (left_contact_reward - right_contact_cost) # cost of contact of right court
# # self.goal_achievement = False
# # # contact only the right side court
# # elif self.right_court_contact_detector and not self.left_court_contact_detector:
# # self.total_reward += 0 + self.ratio * (
# # dist_left_table_reward - right_contact_cost) # cost of contact of right court
# # self.goal_achievement = False
def target_achievement(self, env):
target_coordinate = np.array([-0.5, -0.5])
# net_contact_obj = ["target_ball", "table_tennis_net"]
table_contact_obj = ["target_ball", "table_tennis_table"]
floor_contact_obj = ["target_ball", "floor"]
if 0.78 < env.target_ball_pos[2] < 0.8:
dist_target_virtual = np.linalg.norm(env.target_ball_pos[:2] - target_coordinate)
if self.dist_target_virtual > dist_target_virtual:
self.dist_target_virtual = dist_target_virtual
if -0.07 < env.target_ball_pos[0] < 0.07 and env.sim.data.get_joint_qvel('tar:x') < 0:
if self.ball_z_pos_lowest > env.target_ball_pos[2]:
self.ball_z_pos_lowest = env.target_ball_pos[2].copy()
# if not self.net_contact_detector:
# self.net_contact_detector = self.contact_detection(env, net_contact_obj)
if not self.table_contact_detector:
self.table_contact_detector = self.contact_detection(env, table_contact_obj)
if not self.floor_contact_detector:
self.floor_contact_detector = self.contact_detection(env, floor_contact_obj)
if not self.target_flag:
# Table Contact Reward.
if self.table_contact_detector:
self.total_reward += 1
# only update when the first contact because of the flag
contact_coordinate = env.target_ball_pos[:2].copy()
print("contact table ball coordinate: ", env.target_ball_pos)
logging.info("contact table ball coordinate: {}".format(env.target_ball_pos))
dist_target = np.linalg.norm(contact_coordinate - target_coordinate)
self.total_reward += (1 - np.tanh(dist_target)) * 2
self.target_flag = True
# Net Contact Reward. Precondition: Table Contact exits.
if contact_coordinate[0] < 0:
print("left table contact")
logging.info("~~~~~~~~~~~~~~~left table contact~~~~~~~~~~~~~~~")
self.total_reward += 1
# TODO Z coordinate reward
# self.total_reward += np.maximum(np.tanh(self.ball_z_pos_lowest), 0)
self.goal_achievement = True
else:
print("right table contact")
logging.info("~~~~~~~~~~~~~~~right table contact~~~~~~~~~~~~~~~")
self.total_reward += 0
self.goal_achievement = False
# if self.net_contact_detector:
# self.total_reward += 0
# self.goal_achievement = False
# else:
# self.total_reward += 1
# self.goal_achievement = False
# Floor Contact Reward. Precondition: Table Contact exits.
elif self.floor_contact_detector:
self.total_reward += (1 - np.tanh(self.dist_target_virtual))
self.target_flag = True
self.goal_achievement = False
# No Contact of Floor or Table, flying
else:
pass
# else:
# print("Flag is True already")
self.refresh_highest_reward()
def distance_to_target(self):
pass
@classmethod
def contact_detection(cls, env, goal_contact):
for i in range(env.sim.data.ncon):
contact = env.sim.data.contact[i]
achieved_geom1_name = env.sim.model.geom_id2name(contact.geom1)
achieved_geom2_name = env.sim.model.geom_id2name(contact.geom2)
if np.all([(achieved_geom1_name in goal_contact), (achieved_geom2_name in goal_contact)]):
print("contact of " + achieved_geom1_name + " " + achieved_geom2_name)
return True
else:
return False

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@ -1,136 +0,0 @@
# Copyright 2017 The dm_control Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ============================================================================
# """Soft indicator function evaluating whether a number is within bounds."""
#
# from __future__ import absolute_import
# from __future__ import division
# from __future__ import print_function
# Internal dependencies.
import numpy as np
# The value returned by tolerance() at `margin` distance from `bounds` interval.
_DEFAULT_VALUE_AT_MARGIN = 0.1
def _sigmoids(x, value_at_1, sigmoid):
"""Returns 1 when `x` == 0, between 0 and 1 otherwise.
Args:
x: A scalar or numpy array.
value_at_1: A float between 0 and 1 specifying the output when `x` == 1.
sigmoid: String, choice of sigmoid type.
Returns:
A numpy array with values between 0.0 and 1.0.
Raises:
ValueError: If not 0 < `value_at_1` < 1, except for `linear`, `cosine` and
`quadratic` sigmoids which allow `value_at_1` == 0.
ValueError: If `sigmoid` is of an unknown type.
"""
if sigmoid in ('cosine', 'linear', 'quadratic'):
if not 0 <= value_at_1 < 1:
raise ValueError('`value_at_1` must be nonnegative and smaller than 1, '
'got {}.'.format(value_at_1))
else:
if not 0 < value_at_1 < 1:
raise ValueError('`value_at_1` must be strictly between 0 and 1, '
'got {}.'.format(value_at_1))
if sigmoid == 'gaussian':
scale = np.sqrt(-2 * np.log(value_at_1))
return np.exp(-0.5 * (x*scale)**2)
elif sigmoid == 'hyperbolic':
scale = np.arccosh(1/value_at_1)
return 1 / np.cosh(x*scale)
elif sigmoid == 'long_tail':
scale = np.sqrt(1/value_at_1 - 1)
return 1 / ((x*scale)**2 + 1)
elif sigmoid == 'cosine':
scale = np.arccos(2*value_at_1 - 1) / np.pi
scaled_x = x*scale
return np.where(abs(scaled_x) < 1, (1 + np.cos(np.pi*scaled_x))/2, 0.0)
elif sigmoid == 'linear':
scale = 1-value_at_1
scaled_x = x*scale
return np.where(abs(scaled_x) < 1, 1 - scaled_x, 0.0)
elif sigmoid == 'quadratic':
scale = np.sqrt(1-value_at_1)
scaled_x = x*scale
return np.where(abs(scaled_x) < 1, 1 - scaled_x**2, 0.0)
elif sigmoid == 'tanh_squared':
scale = np.arctanh(np.sqrt(1-value_at_1))
return 1 - np.tanh(x*scale)**2
else:
raise ValueError('Unknown sigmoid type {!r}.'.format(sigmoid))
def tolerance(x, bounds=(0.0, 0.0), margin=0.0, sigmoid='gaussian',
value_at_margin=_DEFAULT_VALUE_AT_MARGIN):
"""Returns 1 when `x` falls inside the bounds, between 0 and 1 otherwise.
Args:
x: A scalar or numpy array.
bounds: A tuple of floats specifying inclusive `(lower, upper)` bounds for
the target interval. These can be infinite if the interval is unbounded
at one or both ends, or they can be equal to one another if the target
value is exact.
margin: Float. Parameter that controls how steeply the output decreases as
`x` moves out-of-bounds.
* If `margin == 0` then the output will be 0 for all values of `x`
outside of `bounds`.
* If `margin > 0` then the output will decrease sigmoidally with
increasing distance from the nearest bound.
sigmoid: String, choice of sigmoid type. Valid values are: 'gaussian',
'linear', 'hyperbolic', 'long_tail', 'cosine', 'tanh_squared'.
value_at_margin: A float between 0 and 1 specifying the output value when
the distance from `x` to the nearest bound is equal to `margin`. Ignored
if `margin == 0`.
Returns:
A float or numpy array with values between 0.0 and 1.0.
Raises:
ValueError: If `bounds[0] > bounds[1]`.
ValueError: If `margin` is negative.
"""
lower, upper = bounds
if lower > upper:
raise ValueError('Lower bound must be <= upper bound.')
if margin < 0:
raise ValueError('`margin` must be non-negative.')
in_bounds = np.logical_and(lower <= x, x <= upper)
if margin == 0:
value = np.where(in_bounds, 1.0, 0.0)
else:
d = np.where(x < lower, lower - x, x - upper) / margin
value = np.where(in_bounds, 1.0, _sigmoids(d, value_at_margin, sigmoid))
return float(value) if np.isscalar(x) else value

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@ -1,49 +0,0 @@
import json
import yaml
import xml.etree.ElementTree as ET
from collections import OrderedDict
from pathlib import Path
def read_json(fname):
fname = Path(fname)
with fname.open('rt') as handle:
return json.load(handle, object_hook=OrderedDict)
def write_json(content, fname):
fname = Path(fname)
with fname.open('wt') as handle:
json.dump(content, handle, indent=4, sort_keys=False)
def read_yaml(fname):
fname = Path(fname)
with fname.open('rt') as handle:
return yaml.load(handle, Loader=yaml.FullLoader)
def write_yaml(content, fname):
fname = Path(fname)
with fname.open('wt') as handle:
yaml.dump(content, handle)
def config_save(dir_path, config):
dir_path = Path(dir_path)
config_path_json = dir_path / "config.json"
config_path_yaml = dir_path / "config.yml"
# .json and .yml file,save 2 version of configuration.
write_json(config, config_path_json)
write_yaml(config, config_path_yaml)
def change_kp_in_xml(kp_list,
model_path="/home/zhou/slow/table_tennis_rl/simulation/gymTableTennis/gym_table_tennis/simple_reacher/robotics/assets/table_tennis/right_arm_actuator.xml"):
tree = ET.parse(model_path)
root = tree.getroot()
# for actuator in root.find("actuator"):
for position, kp in zip(root.iter('position'), kp_list):
position.set("kp", str(kp))
tree.write(model_path)

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@ -1 +0,0 @@
from .mp_wrapper import MPWrapper

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@ -1,38 +0,0 @@
from typing import Tuple, Union
import numpy as np
from alr_envs.black_box.raw_interface_wrapper import RawInterfaceWrapper
class MPWrapper(RawInterfaceWrapper):
@property
def context_mask(self) -> np.ndarray:
# TODO: @Max Filter observations correctly
return np.hstack([
[False] * 7, # Joint Pos
[True] * 2, # Ball pos
[True] * 2 # goal pos
])
@property
def start_pos(self):
return self.self.init_qpos_tt
@property
def current_pos(self) -> Union[float, int, np.ndarray, Tuple]:
return self.sim.data.qpos[:7].copy()
@property
def current_vel(self) -> Union[float, int, np.ndarray, Tuple]:
return self.sim.data.qvel[:7].copy()
@property
def goal_pos(self):
# TODO: @Max I think the default value of returning to the start is reasonable here
raise ValueError("Goal position is not available and has to be learnt based on the environment.")
@property
def dt(self) -> Union[float, int]:
return self.env.dt

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@ -1,184 +0,0 @@
import os
import numpy as np
import mujoco_py
from gym import utils, spaces
from gym.envs.mujoco import MujocoEnv
from alr_envs.alr.mujoco.table_tennis.tt_utils import ball_init
from alr_envs.alr.mujoco.table_tennis.tt_reward import TT_Reward
#TODO: Check for simulation stability. Make sure the code runs even for sim crash
MAX_EPISODE_STEPS = 1375 # (1.25 + 1.5) /0.002
BALL_NAME_CONTACT = "target_ball_contact"
BALL_NAME = "target_ball"
TABLE_NAME = 'table_tennis_table'
FLOOR_NAME = 'floor'
PADDLE_CONTACT_1_NAME = 'bat'
PADDLE_CONTACT_2_NAME = 'bat_back'
RACKET_NAME = 'bat'
# CONTEXT_RANGE_BOUNDS_2DIM = np.array([[-1.2, -0.6], [-0.2, 0.6]])
CONTEXT_RANGE_BOUNDS_2DIM = np.array([[-1.2, -0.6], [-0.2, 0.0]])
CONTEXT_RANGE_BOUNDS_4DIM = np.array([[-1.35, -0.75, -1.25, -0.75], [-0.1, 0.75, -0.1, 0.75]])
class TTEnvGym(MujocoEnv, utils.EzPickle):
def __init__(self, ctxt_dim=2, fixed_goal=False):
model_path = os.path.join(os.path.dirname(__file__), "xml", 'table_tennis_env.xml')
self.ctxt_dim = ctxt_dim
self.fixed_goal = fixed_goal
if ctxt_dim == 2:
self.context_range_bounds = CONTEXT_RANGE_BOUNDS_2DIM
if self.fixed_goal:
self.goal = np.array([-1, -0.1, 0])
else:
self.goal = np.zeros(3) # 2 x,y + 1z
elif ctxt_dim == 4:
self.context_range_bounds = CONTEXT_RANGE_BOUNDS_4DIM
self.goal = np.zeros(3)
else:
raise ValueError("either 2 or 4 dimensional Contexts available")
# has no effect as it is overwritten in init of super
# action_space_low = np.array([-2.6, -2.0, -2.8, -0.9, -4.8, -1.6, -2.2])
# action_space_high = np.array([2.6, 2.0, 2.8, 3.1, 1.3, 1.6, 2.2])
# self.action_space = spaces.Box(low=action_space_low, high=action_space_high, dtype='float64')
self.time_steps = 0
self.init_qpos_tt = np.array([0, 0, 0, 1.5, 0, 0, 1.5, 0, 0, 0])
self.init_qvel_tt = np.zeros(10)
self.reward_func = TT_Reward(self.ctxt_dim)
self.ball_landing_pos = None
self.hit_ball = False
self.ball_contact_after_hit = False
self._ids_set = False
super(TTEnvGym, self).__init__(model_path=model_path, frame_skip=1)
self.ball_id = self.sim.model._body_name2id[BALL_NAME] # find the proper -> not protected func.
self.ball_contact_id = self.sim.model._geom_name2id[BALL_NAME_CONTACT]
self.table_contact_id = self.sim.model._geom_name2id[TABLE_NAME]
self.floor_contact_id = self.sim.model._geom_name2id[FLOOR_NAME]
self.paddle_contact_id_1 = self.sim.model._geom_name2id[PADDLE_CONTACT_1_NAME] # check if we need both or only this
self.paddle_contact_id_2 = self.sim.model._geom_name2id[PADDLE_CONTACT_2_NAME] # check if we need both or only this
self.racket_id = self.sim.model._geom_name2id[RACKET_NAME]
def _set_ids(self):
self.ball_id = self.sim.model._body_name2id[BALL_NAME] # find the proper -> not protected func.
self.table_contact_id = self.sim.model._geom_name2id[TABLE_NAME]
self.floor_contact_id = self.sim.model._geom_name2id[FLOOR_NAME]
self.paddle_contact_id_1 = self.sim.model._geom_name2id[PADDLE_CONTACT_1_NAME] # check if we need both or only this
self.paddle_contact_id_2 = self.sim.model._geom_name2id[PADDLE_CONTACT_2_NAME] # check if we need both or only this
self.racket_id = self.sim.model._geom_name2id[RACKET_NAME]
self.ball_contact_id = self.sim.model._geom_name2id[BALL_NAME_CONTACT]
self._ids_set = True
def _get_obs(self):
ball_pos = self.sim.data.body_xpos[self.ball_id][:2].copy()
goal_pos = self.goal[:2].copy()
obs = np.concatenate([self.sim.data.qpos[:7].copy(), # 7 joint positions
ball_pos,
goal_pos])
return obs
def sample_context(self):
return self.np_random.uniform(self.context_range_bounds[0], self.context_range_bounds[1], size=self.ctxt_dim)
def reset_model(self):
self.set_state(self.init_qpos_tt, self.init_qvel_tt) # reset to initial sim state
self.time_steps = 0
self.ball_landing_pos = None
self.hit_ball = False
self.ball_contact_after_hit = False
if self.fixed_goal:
self.goal = self.goal[:2]
else:
self.goal = self.sample_context()[:2]
if self.ctxt_dim == 2:
initial_ball_state = ball_init(random=False) # fixed velocity, fixed position
elif self.ctxt_dim == 4:
initial_ball_state = ball_init(random=False)#raise NotImplementedError
self.sim.data.set_joint_qpos('tar:x', initial_ball_state[0])
self.sim.data.set_joint_qpos('tar:y', initial_ball_state[1])
self.sim.data.set_joint_qpos('tar:z', initial_ball_state[2])
self.sim.data.set_joint_qvel('tar:x', initial_ball_state[3])
self.sim.data.set_joint_qvel('tar:y', initial_ball_state[4])
self.sim.data.set_joint_qvel('tar:z', initial_ball_state[5])
z_extended_goal_pos = np.concatenate((self.goal[:2], [0.77]))
self.goal = z_extended_goal_pos
self.sim.model.body_pos[5] = self.goal[:3] # Desired Landing Position, Yellow
self.sim.model.body_pos[3] = np.array([0, 0, 0.5]) # Outgoing Ball Landing Position, Green
self.sim.model.body_pos[4] = np.array([0, 0, 0.5]) # Incoming Ball Landing Position, Red
self.sim.forward()
self.reward_func.reset(self.goal) # reset the reward function
self.n_step = 0
return self._get_obs()
def _contact_checker(self, id_1, id_2):
for coni in range(0, self.sim.data.ncon):
con = self.sim.data.contact[coni]
collision = con.geom1 == id_1 and con.geom2 == id_2
collision_trans = con.geom1 == id_2 and con.geom2 == id_1
if collision or collision_trans:
return True
return False
def step(self, action):
if not self._ids_set:
self._set_ids()
done = False
episode_end = False if self.time_steps + 1 < MAX_EPISODE_STEPS else True
if not self.hit_ball:
self.hit_ball = self._contact_checker(self.ball_contact_id, self.paddle_contact_id_1) # check for one side
if not self.hit_ball:
self.hit_ball = self._contact_checker(self.ball_contact_id, self.paddle_contact_id_2) # check for other side
if self.hit_ball:
if not self.ball_contact_after_hit:
if self._contact_checker(self.ball_contact_id, self.floor_contact_id): # first check contact with floor
self.ball_contact_after_hit = True
self.ball_landing_pos = self.sim.data.body_xpos[self.ball_id]
elif self._contact_checker(self.ball_contact_id, self.table_contact_id): # second check contact with table
self.ball_contact_after_hit = True
self.ball_landing_pos = self.sim.data.body_xpos[self.ball_id]
c_ball_pos = self.sim.data.body_xpos[self.ball_id]
racket_pos = self.sim.data.geom_xpos[self.racket_id] # TODO: use this to reach out the position of the paddle?
if self.ball_landing_pos is not None:
done = True
episode_end =True
reward = self.reward_func.get_reward(episode_end, c_ball_pos, racket_pos, self.hit_ball, self.ball_landing_pos)
self.time_steps += 1
# gravity compensation on joints:
#action += self.sim.data.qfrc_bias[:7].copy()
try:
self.do_simulation(action, self.frame_skip)
except mujoco_py.MujocoException as e:
print('Simulation got unstable returning')
done = True
reward = -25
ob = self._get_obs()
info = {"hit_ball": self.hit_ball,
"q_pos": np.copy(self.sim.data.qpos[:7]),
"ball_pos": np.copy(self.sim.data.qpos[7:])}
self.n_step += 1
return ob, reward, done, info # might add some information here ....
def set_context(self, context):
old_state = self.sim.get_state()
qpos = old_state.qpos.copy()
qvel = old_state.qvel.copy()
self.set_state(qpos, qvel)
self.goal = context
z_extended_goal_pos = np.concatenate((self.goal[:self.ctxt_dim], [0.77]))
if self.ctxt_dim == 4:
z_extended_goal_pos = np.concatenate((z_extended_goal_pos, [0.77]))
self.goal = z_extended_goal_pos
self.sim.model.body_pos[5] = self.goal[:3] # TODO: Missing: Setting the desired incomoing landing position
self.sim.forward()
return self._get_obs()

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@ -1,48 +0,0 @@
import numpy as np
class TT_Reward:
def __init__(self, ctxt_dim):
self.ctxt_dim = ctxt_dim
self.c_goal = None # current desired landing point
self.c_ball_traj = []
self.c_racket_traj = []
self.constant = 8
def get_reward(self, episode_end, ball_position, racket_pos, hited_ball, ball_landing_pos):
self.c_ball_traj.append(ball_position.copy())
self.c_racket_traj.append(racket_pos.copy())
if not episode_end:
return 0
else:
# # seems to work for episodic case
min_r_b_dist = np.min(np.linalg.norm(np.array(self.c_ball_traj) - np.array(self.c_racket_traj), axis=1))
if not hited_ball:
return 0.2 * (1 - np.tanh(min_r_b_dist**2))
else:
if ball_landing_pos is None:
min_b_des_b_dist = np.min(np.linalg.norm(np.array(self.c_ball_traj)[:,:2] - self.c_goal[:2], axis=1))
return 2 * (1 - np.tanh(min_r_b_dist ** 2)) + (1 - np.tanh(min_b_des_b_dist**2))
else:
min_b_des_b_land_dist = np.linalg.norm(self.c_goal[:2] - ball_landing_pos[:2])
over_net_bonus = int(ball_landing_pos[0] < 0)
return 2 * (1 - np.tanh(min_r_b_dist ** 2)) + 4 * (1 - np.tanh(min_b_des_b_land_dist ** 2)) + over_net_bonus
# if not hited_ball:
# min_r_b_dist = 1 + np.min(np.linalg.norm(np.array(self.c_ball_traj) - np.array(self.c_racket_traj), axis=1))
# return -min_r_b_dist
# else:
# if ball_landing_pos is None:
# dist_to_des_pos = 1-np.power(np.linalg.norm(self.c_goal - ball_position), 0.75)/self.constant
# else:
# dist_to_des_pos = 1-np.power(np.linalg.norm(self.c_goal - ball_landing_pos), 0.75)/self.constant
# if dist_to_des_pos < -0.2:
# dist_to_des_pos = -0.2
# return -dist_to_des_pos
def reset(self, goal):
self.c_goal = goal.copy()
self.c_ball_traj = []
self.c_racket_traj = []

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@ -1,26 +0,0 @@
import numpy as np
def ball_init(random=False, context_range=None):
if random:
dx = np.random.uniform(-0.1, 0.1) # TODO: clarify these numbers?
dy = np.random.uniform(-0.1, 0.1) # TODO: clarify these numbers?
dz = np.random.uniform(-0.1, 0.1) # TODO: clarify these numbers?
v_x = np.random.uniform(1.7, 1.8)
v_y = np.random.uniform(0.7, 0.8)
v_z = np.random.uniform(0.1, 0.2)
else:
dx = 1
dy = 0
dz = 0.05
v_x = 2.5
v_y = 2
v_z = 0.5
initial_x = 0 + dx - 1.2
initial_y = -0.2 + dy - 0.6
initial_z = 0.3 + dz + 1.5
initial_ball_state = np.array([initial_x, initial_y, initial_z, v_x, v_y, v_z])
return initial_ball_state

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@ -1,12 +0,0 @@
<mujocoinclude>
<actuator>
<motor name="wam/base_motor" joint="wam/base_yaw_joint_right" ctrllimited="true" ctrlrange="-1.0 1.0" gear="150.0"/>
<motor name="wam/shoulder_pitch_motor" joint='wam/shoulder_pitch_joint_right' ctrllimited="true" ctrlrange="-1.0 1.0" gear="125.0"/>
<motor name="wam/shoulder_yaw_motor" joint='wam/shoulder_yaw_joint_right' ctrllimited="true" ctrlrange="-1.0 1.0" gear="40.0"/>
<motor name="wam/elbow_pitch_motor" joint='wam/elbow_pitch_joint_right' ctrllimited="true" ctrlrange="-1.0 1.0" gear="60.0"/>
<motor name="wam/wrist_yaw_motor" joint='wam/wrist_yaw_joint_right' ctrllimited="true" ctrlrange="-1.0 1.0" gear="5.0"/>
<motor name="wam/wrist_pitch_motor" joint='wam/wrist_pitch_joint_right' ctrllimited="true" ctrlrange="-1.0 1.0" gear="5.0"/>
<motor name="wam/palm_yaw_motor" joint='wam/palm_yaw_joint_right' ctrllimited="true" ctrlrange="-1.0 1.0" gear="2.0"/>
</actuator>
</mujocoinclude>

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@ -1,103 +0,0 @@
<mujocoinclue>
<body name="wam/base_link_right" pos="2.1 0 2.0" quat="0 0 1 0" childclass="wam" >
<inertial pos="0 0 0" mass="1" diaginertia="0.1 0.1 0.1"/>
<geom name="base_link_fine" class="viz" mesh="base_link_fine" rgba="0.5 0.5 0.5 0"/>
<geom name="base_link_convex" class="col" mesh="base_link_convex" rgba="0.5 0.5 0.5 1"/>
<body name="wam/shoulder_yaw_link_right" pos="0 0 0.346">
<inertial pos="-0.00443422 -0.00066489 -0.128904" quat="0.69566 0.716713 -0.0354863 0.0334839" mass="5"
diaginertia="0.135089 0.113095 0.0904426"/>
<!-- control 0: 1.6-->
<joint name="wam/base_yaw_joint_right" range="-2.6 2.6" damping="1.98"/>
<geom name="shoulder_link_fine" class="viz" mesh="shoulder_link_fine" rgba="1 1 1 0"/>
<geom name="shoulder_link_convex_decomposition_p1" class="col"
mesh="shoulder_link_convex_decomposition_p1"/>
<geom name="shoulder_link_convex_decomposition_p2" class="col"
mesh="shoulder_link_convex_decomposition_p2"/>
<geom name="shoulder_link_convex_decomposition_p3" class="col"
mesh="shoulder_link_convex_decomposition_p3"/>
<body name="wam/shoulder_pitch_link_right" pos="0 0 0" quat="0.707107 -0.707107 0 0">
<inertial pos="-0.00236981 -0.0154211 0.0310561" quat="0.961794 0.273112 -0.0169316 0.00866592"
mass="3.87494" diaginertia="0.0214195 0.0167127 0.0126452"/> <!--seems off-->
<!-- control 1: 0-->
<joint name="wam/shoulder_pitch_joint_right" range="-2 2" damping="0.55"/>
<geom name="shoulder_pitch_link_fine" class="viz" mesh="shoulder_pitch_link_fine" rgba="1 1 1 0"/>
<geom name="shoulder_pitch_link_convex" class="col" mesh="shoulder_pitch_link_convex"/>
<body name="wam/upper_arm_link_right" pos="0 0 0" quat="0.707107 0.707107 0 0">
<inertial pos="0.00683259 3.309e-005 0.392492" quat="0.647136 0.0170822 0.0143038 0.762049"
mass="2.20228" diaginertia="0.0592718 0.0592207 0.00313419"/>
<!-- control 2: 0-->
<joint name="wam/shoulder_yaw_joint_right" range="-2.8 2.8" damping="1.65"/>
<geom name="upper_arm_link_fine" class="viz" mesh="upper_arm_link_fine" rgba="1 1 1 0"/>
<geom name="upper_arm_link_convex_decomposition_p1" class="col"
mesh="upper_arm_link_convex_decomposition_p1" rgba="0.094 0.48 0.804 1"/>
<geom name="upper_arm_link_convex_decomposition_p2" class="col"
mesh="upper_arm_link_convex_decomposition_p2" rgba="0.094 0.48 0.804 1"/>
<body name="wam/forearm_link_right" pos="0.045 0 0.55" quat="0.707107 -0.707107 0 0">
<inertial pos="-0.0400149 -0.142717 -0.00022942"
quat="0.704281 0.706326 0.0180333 0.0690353" mass="0.500168"
diaginertia="0.0151047 0.0148285 0.00275805"/>
<!-- control 3: 2.4-->
<joint name="wam/elbow_pitch_joint_right" range="-0.9 3.1" damping="0.88"/>
<geom name="elbow_link_fine" class="viz" mesh="elbow_link_fine" rgba="1 1 1 0"/>
<geom name="elbow_link_convex" class="col" mesh="elbow_link_convex"/>
<geom name="forearm_link_fine" class="viz" mesh="forearm_link_fine" pos="-.045 -0.0730 0"
euler="1.57 0 0" rgba="1 1 1 0"/>
<geom name="forearm_link_convex_decomposition_p1" class="col"
mesh="forearm_link_convex_decomposition_p1" pos="-0.045 -0.0730 0"
euler="1.57 0 0" rgba="0.094 0.48 0.804 1"/>
<geom name="forearm_link_convex_decomposition_p2" class="col"
mesh="forearm_link_convex_decomposition_p2" pos="-.045 -0.0730 0"
euler="1.57 0 0" rgba="0.094 0.48 0.804 1"/>
<body name="wam/wrist_yaw_link_right" pos="-0.045 -0.3 0" quat="0.707107 0.707107 0 0">
<inertial pos="8.921e-005 0.00435824 -0.00511217"
quat="0.630602 0.776093 0.00401969 -0.002372" mass="1.05376"
diaginertia="0.000555168 0.00046317 0.000234072"/> <!--this is an approximation-->
<!-- control 4: 0-->
<joint name="wam/wrist_yaw_joint_right" range="-4.8 1.3" damping="0.55"/>
<geom name="wrist_yaw_link_fine" class="viz" mesh="wrist_yaw_link_fine" rgba="1 1 1 0"/>
<geom name="wrist_yaw_link_convex_decomposition_p1" class="col"
mesh="wrist_yaw_link_convex_decomposition_p1"/>
<geom name="wrist_yaw_link_convex_decomposition_p2" class="col"
mesh="wrist_yaw_link_convex_decomposition_p2"/>
<body name="wam/wrist_pitch_link_right" pos="0 0 0" quat="0.707107 -0.707107 0 0">
<inertial pos="-0.00012262 -0.0246834 -0.0170319"
quat="0.630602 0.776093 0.00401969 -0.002372" mass="0.517974"
diaginertia="0.000555168 0.00046317 0.000234072"/>
<!-- control 5: 0-->
<joint name="wam/wrist_pitch_joint_right" range="-1.6 1.6" damping="0.11"/>
<geom name="wrist_pitch_link_fine" class="viz" mesh="wrist_pitch_link_fine"
rgba="1 1 1 0"/>
<geom name="wrist_pitch_link_convex_decomposition_p1" rgba="1 0.5 0.313 1"
class="col" mesh="wrist_pitch_link_convex_decomposition_p1"/>
<geom name="wrist_pitch_link_convex_decomposition_p2" rgba="1 0.5 0.313 1"
class="col" mesh="wrist_pitch_link_convex_decomposition_p2"/>
<geom name="wrist_pitch_link_convex_decomposition_p3" rgba="1 0.5 0.313 1"
class="col" mesh="wrist_pitch_link_convex_decomposition_p3"/>
<body name="wam/wrist_palm_link_right" pos="0 0 0" quat="0.707107 0.707107 0 0">
<inertial pos="0 0 0.055" quat="0.707107 0 0 0.707107" mass="0.0828613"
diaginertia="0.00020683 0.00010859 0.00010851"/>
<!-- control 6: 1.8-->
<joint name="wam/palm_yaw_joint_right" range="-2.2 2.2" damping="0.11"/>
<geom name="wrist_palm_link_fine" class="viz" mesh="wrist_palm_link_fine"
rgba="1 1 1 0"/>
<geom name="wrist_palm_link_convex" class="col" mesh="wrist_palm_link_convex"/>
<!-- EE=wam/paddle, configure name to the end effector name-->
<body name="EE" pos="0 0 0.26" childclass="contact_geom">
<geom name="bat" type="cylinder" size="0.075 0.005" rgba="1 0 0 1"
quat="0.71 0 0.71 0"/>
<geom name="bat_back" type="cylinder" size="0.0749 0.0025" rgba="0 1 0 1"
quat="0.71 0 0.71 0" pos="-0.0026 0 0"/>
<geom name="wam/paddle_handle" type="box" size="0.005 0.01 0.05" pos="0 0 -0.08"
rgba="1 1 1 1"/>
<!-- Extract information for sampling goals.-->
<site name="wam/paddle_center" pos="0 0 0" rgba="1 1 1 1" size="0.00001"/>
</body>
</body>
</body>
</body>
</body>
</body>
</body>
</body>
</body>
</mujocoinclue>

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@ -1,30 +0,0 @@
<mujocoinclude>
<body name="table_tennis_table" pos="0 0 0">
<geom class="viz" name="table_base_1" pos="1 0.7 0.375" rgba="1 1 1 1" size="0.05 0.05 .375" type="box" />
<geom class="viz" name="table_base_2" pos="1 -0.7 0.375" rgba="1 1 1 1" size="0.05 0.05 .375" type="box" />
<geom class="viz" name="table_base_3" pos="-1 -0.7 0.375" rgba="1 1 1 1" size="0.05 0.05 .375" type="box" />
<geom class="viz" name="table_base_4" pos="-1 0.7 0.375" rgba="1 1 1 1" size="0.05 0.05 .375" type="box" />
<body name="table_top" pos="0 0 0.76">
<geom class="contact_geom" name="table_tennis_table" pos="0 0 0" rgba="0 0 0.5 1" size="1.37 .7625 .01" type="box" />
<site name="left_up_corner" pos="-1.37 .7625 0.01" rgba="1 1 1 1" size="0.00001" />
<site name="middle_up_corner" pos="0 .7625 0.01" rgba="1 1 1 1" size="0.00001" />
<site name="left_down_corner" pos="-1.37 -0.7625 0.01" rgba="1 1 1 1" size="0.00001" />
<site name="middle_down_corner" pos="0 -.7625 0.01" rgba="1 1 1 1" size="0.00001" />
<geom class="contact_geom" material="floor_plane" name="table_te_context_spacennis_net" pos="0 0 0.08625" rgba="0 0 1 0.5" size="0.01 0.915 0.07625" type="box" />
<geom class="viz" name="left_while_line" pos="0 -0.7425 0.01" rgba="1 1 1 1" size="1.37 .02 .001" type="box" />
<geom class="viz" name="center_while_line" pos="0 0 0.01" rgba="1 1 1 1" size="1.37 .01 .001" type="box" />
<geom class="viz" name="right_while_line" pos="0 0.7425 0.01" rgba="1 1 1 1" size="1.37 .02 .001" type="box" />
<geom class="viz" name="right_side_line" pos="1.35 0 0.01" rgba="1 1 1 1" size="0.02 .7625 .001" type="box" />
<geom class="viz" name="left_side_line" pos="-1.35 0 0.01" rgba="1 1 1 1" size="0.02 .7625 .001" type="box" />
</body>
<body name="achieved_pos" pos="0 0 0.5">
<geom class="viz" name="achieved_point_geom" pos="0 0 0" rgba="0 1 0 1" size="0.02 0.001" type="cylinder" />
</body>
<body name="right_achieved_pos" pos="0 0 0.5">
<geom class="viz" name="hitting_achieved_point_geom" pos="0 0 0" rgba="1 0 0 1" size="0.02 0.001" type="cylinder" />
</body>
<body name="target_point" pos="0 0 0.5">
<geom class="viz" name="target_point_geom" pos="0 0 0" rgba="1 1 0 1" size="0.02 0.001" type="cylinder" />
</body>
</body>
</mujocoinclude>

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@ -1,10 +0,0 @@
<mujocoinclude>
<body name="target_ball" pos="0 0 0">
<joint axis="1 0 0" damping="0.0" name="tar:x" pos="0 0 0" stiffness="0" type="slide" frictionloss="0"/>
<joint axis="0 1 0" damping="0.0" name="tar:y" pos="0 0 0" stiffness="0" type="slide" frictionloss="0"/>
<joint axis="0 0 1" damping="0.0" name="tar:z" pos="0 0 0" stiffness="0" type="slide" frictionloss="0"/>
<geom size="0.025 0.025 0.025" type="sphere" condim="4" name="target_ball_contact" rgba="1 1 0 1" mass="0.1"
friction="0.1 0.1 0.1" solimp="0.9 0.95 0.001 0.5 2" solref="0.1 0.03" priority="1"/>
<site name="target_ball" pos="0 0 0" size="0.02 0.02 0.02" rgba="1 0 0 1" type="sphere"/>
</body>
</mujocoinclude>

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@ -1,47 +0,0 @@
<mujocoinclude>
<actuator>
<!-- <position ctrlrange="-2.6 2.6" joint="wam/base_yaw_joint_right" kp="100.0" />-->
<!-- <position ctrlrange="-1.985 1.985" joint="wam/shoulder_pitch_joint_right" kp="162.0" />-->
<!-- <position ctrlrange="-2.8 2.8" joint="wam/shoulder_yaw_joint_right" kp="100.0" />-->
<!-- <position ctrlrange="-0.9 3.14159" joint="wam/elbow_pitch_joint_right" kp="122.0" />-->
<!-- <position ctrlrange="-4.55 1.25" joint="wam/wrist_yaw_joint_right" kp="100.0" />-->
<!-- <position ctrlrange="-1.5707 1.5707" joint="wam/wrist_pitch_joint_right" kp="102.0" />-->
<!-- <position ctrlrange="-3 3" joint="wam/palm_yaw_joint_right" kp="100.0" />-->
<!-- <position ctrlrange="-2.6 2.6" joint="wam/base_yaw_joint_right" kp="151.0" ctrllimited="true"/>-->
<!-- <position ctrlrange="-1.985 1.985" joint="wam/shoulder_pitch_joint_right" kp="125.0" ctrllimited="true"/>-->
<!-- <position ctrlrange="-2.8 2.8" joint="wam/shoulder_yaw_joint_right" kp="122.0" ctrllimited="true"/>-->
<!-- <position ctrlrange="-0.9 3.14159" joint="wam/elbow_pitch_joint_right" kp="121.0" ctrllimited="true"/>-->
<!-- <position ctrlrange="-4.55 1.25" joint="wam/wrist_yaw_joint_right" kp="99.0" ctrllimited="true"/>-->
<!-- <position ctrlrange="-1.5707 1.5707" joint="wam/wrist_pitch_joint_right" kp="103.0" ctrllimited="true"/>-->
<!-- <position ctrlrange="-3 3" joint="wam/palm_yaw_joint_right" kp="99.0" ctrllimited="true"/>-->
<!-- <position ctrlrange="-2.6 2.6" joint="wam/base_yaw_joint_right" kp="100.0" ctrllimited="true"/>-->
<!-- <position ctrlrange="-1.985 1.985" joint="wam/shoulder_pitch_joint_right" kp="600.0" ctrllimited="true"/>-->
<!-- <position ctrlrange="-2.8 2.8" joint="wam/shoulder_yaw_joint_right" kp="122.0" ctrllimited="true"/>-->
<!-- <position ctrlrange="-0.9 3.14159" joint="wam/elbow_pitch_joint_right" kp="500.0" ctrllimited="true"/>-->
<!-- <position ctrlrange="-4.55 1.25" joint="wam/wrist_yaw_joint_right" kp="99.0" ctrllimited="true"/>-->
<!-- <position ctrlrange="-1.5707 1.5707" joint="wam/wrist_pitch_joint_right" kp="103.0" ctrllimited="true"/>-->
<!-- <position ctrlrange="-3 3" joint="wam/palm_yaw_joint_right" kp="99.0" ctrllimited="true"/>-->
<position ctrlrange="-2.6 2.6" joint="wam/base_yaw_joint_right" kp="800.0" ctrllimited="true"/>
<position ctrlrange="-1.985 1.985" joint="wam/shoulder_pitch_joint_right" kp="800.0" ctrllimited="true"/>
<position ctrlrange="-2.8 2.8" joint="wam/shoulder_yaw_joint_right" kp="800.0" ctrllimited="true"/>
<position ctrlrange="-0.9 3.14159" joint="wam/elbow_pitch_joint_right" kp="800.0" ctrllimited="true"/>
<position ctrlrange="-4.55 1.25" joint="wam/wrist_yaw_joint_right" kp="100.0" ctrllimited="true"/>
<position ctrlrange="-1.5707 1.5707" joint="wam/wrist_pitch_joint_right" kp="1000.0" ctrllimited="true"/>
<position ctrlrange="-3 3" joint="wam/palm_yaw_joint_right" kp="100.0" ctrllimited="true"/>
<!-- <position ctrlrange="-2.6 2.6" joint="wam/base_yaw_joint_right" kp="1600.0" ctrllimited="true"/>-->
<!--&lt;!&ndash; <velocity ctrlrange="-50 50" joint="wam/base_yaw_joint_right" kv="100" ctrllimited="true"/>&ndash;&gt;-->
<!-- <position ctrlrange="-1.985 1.985" joint="wam/shoulder_pitch_joint_right" kp="2000.0" ctrllimited="true"/>-->
<!-- <position ctrlrange="-2.8 2.8" joint="wam/shoulder_yaw_joint_right" kp="800.0" ctrllimited="true"/>-->
<!-- <position ctrlrange="-0.9 3.14159" joint="wam/elbow_pitch_joint_right" kp="1200.0" ctrllimited="true"/>-->
<!-- <position ctrlrange="-4.55 1.25" joint="wam/wrist_yaw_joint_right" kp="100.0" ctrllimited="true"/>-->
<!-- <position ctrlrange="-1.5707 1.5707" joint="wam/wrist_pitch_joint_right" kp="2000.0" ctrllimited="true"/>-->
<!-- <position ctrlrange="-3 3" joint="wam/palm_yaw_joint_right" kp="100.0" ctrllimited="true"/>-->
</actuator>
</mujocoinclude>

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@ -1,46 +0,0 @@
<mujocoinclude>
<default>
<default class="wam">
<joint type="hinge" limited="true" pos="0 0 0" axis="0 0 1"/>
</default>
<default class="viz">
<geom type="mesh" contype="0" conaffinity="0" group="1" rgba="1 1 1 1"/>
</default>
<default class="col">
<geom type="mesh" contype="0" conaffinity="1" group="0" rgba="1 1 1 1"/>
</default>
<default class="contact_geom">
<geom condim="4" friction="0.1 0.1 0.1" margin="0" solimp="1 1 0" solref="0.1 0.03"/>
</default>
</default>
<asset>
<mesh file="base_link_fine.stl"/>
<mesh file="base_link_convex.stl"/>
<mesh file="shoulder_link_fine.stl"/>
<mesh file="shoulder_link_convex_decomposition_p1.stl"/>
<mesh file="shoulder_link_convex_decomposition_p2.stl"/>
<mesh file="shoulder_link_convex_decomposition_p3.stl"/>
<mesh file="shoulder_pitch_link_fine.stl"/>
<mesh file="shoulder_pitch_link_convex.stl"/>
<mesh file="upper_arm_link_fine.stl"/>
<mesh file="upper_arm_link_convex_decomposition_p1.stl"/>
<mesh file="upper_arm_link_convex_decomposition_p2.stl"/>
<mesh file="elbow_link_fine.stl"/>
<mesh file="elbow_link_convex.stl"/>
<mesh file="forearm_link_fine.stl"/>
<mesh file="forearm_link_convex_decomposition_p1.stl"/>
<mesh file="forearm_link_convex_decomposition_p2.stl"/>
<mesh file="wrist_yaw_link_fine.stl"/>
<mesh file="wrist_yaw_link_convex_decomposition_p1.stl"/>
<mesh file="wrist_yaw_link_convex_decomposition_p2.stl"/>
<mesh file="wrist_pitch_link_fine.stl"/>
<mesh file="wrist_pitch_link_convex_decomposition_p1.stl"/>
<mesh file="wrist_pitch_link_convex_decomposition_p2.stl"/>
<mesh file="wrist_pitch_link_convex_decomposition_p3.stl"/>
<mesh file="wrist_palm_link_fine.stl"/>
<mesh file="wrist_palm_link_convex.stl"/>
<texture builtin="checker" height="512" name="texplane" rgb1=".2 .3 .4" rgb2=".1 0.15 0.2" type="2d"
width="512"/>
<material name="floor_plane" reflectance="0.5" texrepeat="1 1" texture="texplane" texuniform="true"/>
</asset>
</mujocoinclude>

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@ -1,18 +0,0 @@
<mujoco model="table_tennis(v0.1)">
<compiler angle="radian" coordinate="local" meshdir="../../meshes/wam" />
<option gravity="0 0 -9.81" timestep="0.002">
<flag warmstart="enable" />
</option>
<custom>
<numeric data="0 0 0 0 0 0 0" name="START_ANGLES" />
</custom>
<include file="shared.xml" />
<worldbody>
<light cutoff="60" diffuse="1 1 1" dir="-.1 -.2 -1.3" directional="true" exponent="1" pos=".1 .2 1.3" specular=".1 .1 .1" />
<geom conaffinity="1" contype="1" material="floor_plane" name="floor" pos="0 0 0" size="10 5 1" type="plane" />
<include file="include_table.xml" />
<include file="include_barrett_wam_7dof_right.xml" />
<include file="include_target_ball.xml" />
</worldbody>
<include file="include_7_motor_actuator.xml" />
</mujoco>

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@ -1,23 +0,0 @@
from typing import Tuple, Union
import numpy as np
from alr_envs.black_box.raw_interface_wrapper import RawInterfaceWrapper
class MPWrapper(RawInterfaceWrapper):
@property
def context_mask(self):
return np.hstack([
[False] * 17,
[True] # goal pos
])
@property
def current_pos(self) -> Union[float, int, np.ndarray]:
return self.env.data.qpos[3:9].copy()
@property
def current_vel(self) -> Union[float, int, np.ndarray, Tuple]:
return self.env.data.qvel[3:9].copy()