54 lines
1.7 KiB
Python
54 lines
1.7 KiB
Python
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import os
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import numpy as np
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from gym import utils
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from gym.envs.mujoco import mujoco_env
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from alr_envs.utils.utils import angle_normalize
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class BalancingEnv(mujoco_env.MujocoEnv, utils.EzPickle):
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def __init__(self, n_links=5):
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utils.EzPickle.__init__(**locals())
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self.n_links = n_links
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if n_links == 5:
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file_name = 'reacher_5links.xml'
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elif n_links == 7:
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file_name = 'reacher_7links.xml'
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else:
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raise ValueError(f"Invalid number of links {n_links}, only 5 or 7 allowed.")
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mujoco_env.MujocoEnv.__init__(self, os.path.join(os.path.dirname(__file__), "assets", file_name), 2)
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def step(self, a):
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angle = angle_normalize(np.sum(self.sim.data.qpos.flat[:self.n_links]), type="rad")
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reward = - np.abs(angle)
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self.do_simulation(a, self.frame_skip)
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ob = self._get_obs()
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done = False
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return ob, reward, done, dict(angle=angle, end_effector=self.get_body_com("fingertip").copy())
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def viewer_setup(self):
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self.viewer.cam.trackbodyid = 1
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def reset_model(self):
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# This also generates a goal, we however do not need/use it
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qpos = self.np_random.uniform(low=-0.1, high=0.1, size=self.model.nq) + self.init_qpos
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qpos[-2:] = 0
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qvel = self.init_qvel + self.np_random.uniform(low=-.005, high=.005, size=self.model.nv)
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qvel[-2:] = 0
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self.set_state(qpos, qvel)
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return self._get_obs()
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def _get_obs(self):
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theta = self.sim.data.qpos.flat[:self.n_links]
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return np.concatenate([
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np.cos(theta),
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np.sin(theta),
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self.sim.data.qvel.flat[:self.n_links], # this is angular velocity
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])
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