lots of new stuff...

This commit is contained in:
Maximilian Huettenrauch
2021-02-05 17:10:03 +01:00
parent cab2c249bb
commit 07195fa2dc
108 changed files with 1086 additions and 51 deletions
@@ -0,0 +1,366 @@
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<joint name="J0_13" pos="-0.00535 0 0" axis="0 1 0" group="3" limited="false" damping="0.0001" frictionloss="0" />
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<joint name="J0_14" pos="-0.00535 0 0" axis="0 1 0" group="3" limited="false" damping="0.0001" frictionloss="0" />
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<joint name="J0_15" pos="-0.00535 0 0" axis="0 1 0" group="3" limited="false" damping="0.0001" frictionloss="0" />
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<joint name="J0_16" pos="-0.00535 0 0" axis="0 1 0" group="3" limited="false" damping="0.0001" frictionloss="0" />
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<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" />
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<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" />
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<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" />
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<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" />
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<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" />
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<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" />
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<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" />
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<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" />
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<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" />
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<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" />
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<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="0.021" rgba="0.8 0.2 0.1 1"/>
</body>
</body>
</body>
</body>
</body>
</body>
</body>
</body>
</body>
</body>
</body>
</body>
</body>
</body>
</body>
</body>
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</body>
</body>
</body>
</body>
</body>
</body>
</body>
</body>
</body>
</body>
</body>
</body>
</body>
</body>
<site name="context_point" pos="0 0.05 0.1165" 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 ctrlrange="-150 150" joint="wam/base_yaw_joint"/>
<motor ctrlrange="-125 125" joint="wam/shoulder_pitch_joint"/>
<motor ctrlrange="-40 40" joint="wam/shoulder_yaw_joint"/>
<motor ctrlrange="-60 60" joint="wam/elbow_pitch_joint"/>
<motor ctrlrange="-5 5" joint="wam/wrist_yaw_joint"/>
<motor ctrlrange="-5 5" joint="wam/wrist_pitch_joint"/>
<motor ctrlrange="-2 2" joint="wam/palm_yaw_joint"/>
<!-- <position ctrllimited="true" ctrlrange="-2.6 2.6" joint="wam/base_yaw_joint" kp="151.0"/>-->
<!-- <position ctrllimited="true" ctrlrange="-1.985 1.985" joint="wam/shoulder_pitch_joint" kp="125.0"/>-->
<!-- <position ctrllimited="true" ctrlrange="-2.8 2.8" joint="wam/shoulder_yaw_joint" kp="122.0"/>-->
<!-- <position ctrllimited="true" ctrlrange="-0.9 3.14159" joint="wam/elbow_pitch_joint" kp="121.0"/>-->
<!-- <position ctrllimited="true" ctrlrange="-4.55 1.25" joint="wam/wrist_yaw_joint" kp="99.0"/>-->
<!-- <position ctrllimited="true" ctrlrange="-1.5707 1.5707" joint="wam/wrist_pitch_joint" kp="103.0"/>-->
<!-- <position ctrllimited="true" ctrlrange="-3 3" joint="wam/palm_yaw_joint" kp="99.0"/>-->
<!-- <velocity joint="wam/base_yaw_joint" kv="7.0"/>-->
<!-- <velocity joint="wam/shoulder_pitch_joint" kv="15.0"/>-->
<!-- <velocity joint="wam/shoulder_yaw_joint" kv="5.0"/>-->
<!-- <velocity joint="wam/elbow_pitch_joint" kv="2.5"/>-->
<!-- <velocity joint="wam/wrist_yaw_joint" kv="0.3"/>-->
<!-- <velocity joint="wam/wrist_pitch_joint" kv="0.3"/>-->
<!-- <velocity joint="wam/palm_yaw_joint" kv="0.05"/>-->
</actuator>
</mujoco>
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@@ -0,0 +1,117 @@
from gym.envs.mujoco import mujoco_env
from gym import utils
import os
import numpy as np
from alr_envs.mujoco.ball_in_a_cup.ball_in_a_cup_reward import BallInACupReward
import mujoco_py
class ALRBallInACupEnv(mujoco_env.MujocoEnv, utils.EzPickle):
def __init__(self, ):
self._steps = 0
self.xml_path = os.path.join(os.path.dirname(os.path.abspath(__file__)), "assets",
"ball-in-a-cup_base" + ".xml")
self.sim_time = 8 # seconds
self.sim_steps = int(self.sim_time / (0.0005 * 4)) # circular dependency.. sim.dt <-> mujocoenv init <-> reward fct
self.reward_function = BallInACupReward(self.sim_steps)
self.start_pos = np.array([0.0, 0.58760536, 0.0, 1.36004913, 0.0, -0.32072943, -1.57])
self._q_pos = []
utils.EzPickle.__init__(self)
mujoco_env.MujocoEnv.__init__(self, os.path.join(os.path.dirname(__file__), "assets", "ball-in-a-cup_base.xml"),
frame_skip=4)
def reset_model(self):
start_pos = self.init_qpos.copy()
start_pos[0:7] = self.start_pos
start_vel = np.zeros_like(start_pos)
self.set_state(start_pos, start_vel)
self._steps = 0
self.reward_function.reset()
self._q_pos = []
def do_simulation(self, ctrl, n_frames):
self.sim.data.ctrl[:] = ctrl
for _ in range(n_frames):
try:
self.sim.step()
except mujoco_py.builder.MujocoException as e:
# print("Error in simulation: " + str(e))
# error = True
# Copy the current torque as if it would have been applied until the end of the trajectory
# for i in range(k + 1, sim_time):
# torques.append(trq)
return True
return False
def step(self, a):
# Apply gravity compensation
if not np.all(self.sim.data.qfrc_applied[:7] == self.sim.data.qfrc_bias[:7]):
self.sim.data.qfrc_applied[:7] = self.sim.data.qfrc_bias[:7]
reward_dist = 0.0
angular_vel = 0.0
# if self._steps >= self.steps_before_reward:
# vec = self.get_body_com("fingertip") - self.get_body_com("target")
# reward_dist -= self.reward_weight * np.linalg.norm(vec)
# angular_vel -= np.linalg.norm(self.sim.data.qvel.flat[:self.n_links])
reward_ctrl = - np.square(a).sum()
# reward_balance = - self.balance_weight * np.abs(
# angle_normalize(np.sum(self.sim.data.qpos.flat[:self.n_links]), type="rad"))
#
# reward = reward_dist + reward_ctrl + angular_vel + reward_balance
# self.do_simulation(a, self.frame_skip)
crash = self.do_simulation(a, self.frame_skip)
self._q_pos.append(self.sim.data.qpos[0:7].ravel().copy())
ob = self._get_obs()
if not crash:
reward, success, collision = self.reward_function.compute_reward(a, self.sim, self._steps)
done = success or self._steps == self.sim_steps - 1 or collision
self._steps += 1
else:
reward = -1000
done = True
return ob, reward, done, dict(reward_dist=reward_dist, reward_ctrl=reward_ctrl,
velocity=angular_vel, # reward_balance=reward_balance,
# end_effector=self.get_body_com("fingertip").copy(),
goal=self.goal if hasattr(self, "goal") else None,
traj=self._q_pos)
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],
])
if __name__ == "__main__":
env = ALRBallInACupEnv()
env.reset()
for i in range(2000):
# objective.load_result("/tmp/cma")
# test with random actions
# ac = 0.0 * env.action_space.sample()
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()
@@ -0,0 +1,127 @@
import numpy as np
class BallInACupReward:
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.ctxt_id = None
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_final = None
self.costs = None
self.reset()
def reset(self):
self.ball_traj = np.zeros(shape=(self.sim_time, 3))
self.dists = []
self.dists_final = []
self.costs = []
def compute_reward(self, action, sim, step):
self.ctxt_id = sim.model._site_name2id['context_point']
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]
ball_in_cup = self.check_ball_in_cup(sim, self.ball_collision_id)
# 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))
# dists_ctxt.append(np.linalg.norm(ball_pos - ctxt))
self.ball_traj[step, :] = ball_pos
if self.check_collision(sim):
return -1000, False, True
# self._get_cost(ball_pos, goal_pos, goal_final_pos, action,
# sim.data.get_site_xpos('context_point').copy(), step)
# min_dist = np.min(self.dists)
# dist_final = self.dists_final[-1]
action_cost = np.sum(np.square(action))
# cost = self.get_stage_wise_cost(ball_in_cup, min_dist, self.dists_final[-1]) # , self.dists_ctxt[-1])
if step == self.sim_time - 1:
min_dist = np.min(self.dists)
dist_final = self.dists_final[-1]
cost = 0.5 * min_dist + 0.5 * dist_final
# cost = 3 + 2 * (0.5 * min_dist ** 2 + 0.5 * dist_final ** 2)
reward = np.exp(-2 * min_dist) - 1e-5 * action_cost
success = dist_final < 0.05 and min_dist < 0.05
else:
cost = 0
reward = - 1e-5 * action_cost
success = False
# action_cost = np.mean(np.sum(np.square(torques), axis=1), axis=0)
return reward, success, False
def get_stage_wise_cost(self, ball_in_cup, min_dist, dist_final): #, dist_to_ctxt):
# stop_sim = False
cost = 3 + 2 * (0.5 * min_dist ** 2 + 0.5 * dist_final ** 2)
# if not ball_in_cup:
# # cost = 3 + 2*(0.5 * min_dist + 0.5 * dist_final)
# cost = 3 + 2*(0.5 * min_dist**2 + 0.5 * dist_final**2)
# else:
# # cost = 2*dist_to_ctxt
# cost = 2*dist_to_ctxt**2
# stop_sim = True
# # print(dist_to_ctxt-0.02)
# print('Context Distance:', dist_to_ctxt)
return cost
def _get_cost(self, ball_pos, goal_pos, goal_pos_final, u, ctxt, t):
cost = 0
if t == self.sim_time*0.8:
dist = 0.5*np.linalg.norm(goal_pos-ball_pos)**2 + 0.5*np.linalg.norm(goal_pos_final-ball_pos)**2
# dist_ctxt = np.linalg.norm(ctxt-goal_pos)**2
cost = dist # +dist_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
@@ -0,0 +1,210 @@
from gym.envs.mujoco import mujoco_env
from gym import utils, spaces
import os
import numpy as np
from alr_envs.mujoco.ball_in_a_cup.ball_in_a_cup_reward import BallInACupReward
import mujoco_py
class ALRBallInACupEnv(mujoco_env.MujocoEnv, utils.EzPickle):
def __init__(self, pd_control=True):
self._steps = 0
self.pd_control = pd_control
self.xml_path = os.path.join(os.path.dirname(os.path.abspath(__file__)), "assets",
"ball-in-a-cup_base" + ".xml")
self.sim_time = 8 # seconds
self.sim_steps = int(self.sim_time / (0.0005 * 4)) # circular dependency.. sim.dt <-> mujocoenv init <-> reward fct
self.reward_function = BallInACupReward(self.sim_steps)
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.start_pos = np.array([0.58760536, 1.36004913, -0.32072943])
self._q_pos = []
self._q_vel = []
# self.weight_matrix_scale = 50
self.p_gains = 1*np.array([200, 300, 100, 100, 10, 10, 2.5])
self.d_gains = 1*np.array([7, 15, 5, 2.5, 0.3, 0.3, 0.05])
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])
utils.EzPickle.__init__(self)
mujoco_env.MujocoEnv.__init__(self, os.path.join(os.path.dirname(__file__), "assets", "ball-in-a-cup_base.xml"),
frame_skip=4)
@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_model(self):
init_pos_all = self.init_qpos.copy()
init_pos_robot = self.start_pos
init_vel = np.zeros_like(init_pos_all)
ball_id = self.sim.model._body_name2id["ball"]
goal_final_id = self.sim.model._site_name2id["cup_goal_final"]
# self.set_state(start_pos, start_vel)
self._steps = 0
self.reward_function.reset()
self._q_pos = []
self._q_vel = []
# Reset the system
self.sim.data.qpos[:] = init_pos_all
self.sim.data.qvel[:] = init_vel
self.sim.data.qpos[0:7] = init_pos_robot
self.sim.step()
self.sim.data.qpos[:] = init_pos_all
self.sim.data.qvel[:] = init_vel
self.sim.data.qpos[0:7] = init_pos_robot
self.sim.data.body_xpos[ball_id, :] = np.copy(self.sim.data.site_xpos[goal_final_id, :]) - np.array([0., 0., 0.329])
# Stabilize the system around the initial position
for i in range(0, 2000):
self.sim.data.qpos[7:] = 0.
self.sim.data.qvel[7:] = 0.
# self.sim.data.qpos[7] = -0.2
cur_pos = self.sim.data.qpos[0:7].copy()
cur_vel = self.sim.data.qvel[0:7].copy()
trq = self.p_gains * (init_pos_robot - cur_pos) + self.d_gains * (np.zeros_like(init_pos_robot) - cur_vel)
self.sim.data.qfrc_applied[0:7] = trq + self.sim.data.qfrc_bias[:7].copy()
self.sim.step()
# self.render()
for i in range(0, 2000):
cur_pos = self.sim.data.qpos[0:7].copy()
cur_vel = self.sim.data.qvel[0:7].copy()
trq = self.p_gains * (init_pos_robot - cur_pos) + self.d_gains * (np.zeros_like(init_pos_robot) - cur_vel)
self.sim.data.qfrc_applied[0:7] = trq + self.sim.data.qfrc_bias[:7].copy()
self.sim.step()
# self.render()
def do_simulation(self, ctrl, n_frames):
# cur_pos = self.sim.data.qpos[0:7].copy()
# cur_vel = self.sim.data.qvel[0:7].copy()
# des_pos = ctrl[:7]
# des_vel = ctrl[7:]
# trq = self.p_gains * (des_pos - cur_pos) + self.d_gains * (des_vel - cur_vel)
if self.pd_control:
self.sim.data.qfrc_applied[0:7] = ctrl + self.sim.data.qfrc_bias[:7].copy()
else:
self.sim.data.ctrl[:] = ctrl
for _ in range(n_frames):
try:
self.sim.step()
except mujoco_py.builder.MujocoException as e:
print("Error in simulation: " + str(e))
# error = True
# Copy the current torque as if it would have been applied until the end of the trajectory
# for i in range(k + 1, sim_time):
# torques.append(trq)
return True
return False
def step(self, a):
# Apply gravity compensation
# if not np.all(self.sim.data.qfrc_applied[:7] == self.sim.data.qfrc_bias[:7]):
# self.sim.data.qfrc_applied[:7] = self.sim.data.qfrc_bias[:7]
reward_dist = 0.0
angular_vel = 0.0
# if self._steps >= self.steps_before_reward:
# vec = self.get_body_com("fingertip") - self.get_body_com("target")
# reward_dist -= self.reward_weight * np.linalg.norm(vec)
# angular_vel -= np.linalg.norm(self.sim.data.qvel.flat[:self.n_links])
reward_ctrl = - np.square(a).sum()
# reward_balance = - self.balance_weight * np.abs(
# angle_normalize(np.sum(self.sim.data.qpos.flat[:self.n_links]), type="rad"))
#
# reward = reward_dist + reward_ctrl + angular_vel + reward_balance
# self.do_simulation(a, self.frame_skip)
joint_cons_viol = self.check_traj_in_joint_limits()
crash = self.do_simulation(a, self.frame_skip)
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 and not joint_cons_viol:
reward, success, collision = self.reward_function.compute_reward(a, self.sim, self._steps)
done = success or self._steps == self.sim_steps - 1 or collision
self._steps += 1
else:
reward = -1000
done = True
return ob, reward, done, dict(reward_dist=reward_dist, reward_ctrl=reward_ctrl,
velocity=angular_vel, # reward_balance=reward_balance,
# end_effector=self.get_body_com("fingertip").copy(),
goal=self.goal if hasattr(self, "goal") else None,
traj=self._q_pos)
def check_traj_in_joint_limits(self):
return any(self.current_pos > self.j_max) or any(self.current_pos < self.j_min)
def check_collision(self):
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
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],
])
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
if __name__ == "__main__":
env = ALRBallInACupEnv()
env.reset()
env.render()
for i in range(4000):
# objective.load_result("/tmp/cma")
# test with random actions
# ac = 0.1 * env.action_space.sample()
# ac = -np.array([i, i, i]) / 10000 + np.array([env.start_pos[1], env.start_pos[3], env.start_pos[5]])
ac = np.array([0., -0.1, 0, 0, 0, 0, 0])
# ac[0] += np.pi/2
obs, rew, d, info = env.step(ac)
env.render()
print(rew)
if d:
break
env.close()