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| import numpy as np | |
| from gym import utils | |
| from gym.envs.mujoco import MuJocoPyEnv | |
| from gym.spaces import Box | |
| class Walker2dEnv(MuJocoPyEnv, utils.EzPickle): | |
| metadata = { | |
| "render_modes": [ | |
| "human", | |
| "rgb_array", | |
| "depth_array", | |
| ], | |
| "render_fps": 125, | |
| } | |
| def __init__(self, **kwargs): | |
| observation_space = Box(low=-np.inf, high=np.inf, shape=(17,), dtype=np.float64) | |
| MuJocoPyEnv.__init__( | |
| self, "walker2d.xml", 4, observation_space=observation_space, **kwargs | |
| ) | |
| utils.EzPickle.__init__(self, **kwargs) | |
| def step(self, a): | |
| posbefore = self.sim.data.qpos[0] | |
| self.do_simulation(a, self.frame_skip) | |
| posafter, height, ang = self.sim.data.qpos[0:3] | |
| alive_bonus = 1.0 | |
| reward = (posafter - posbefore) / self.dt | |
| reward += alive_bonus | |
| reward -= 1e-3 * np.square(a).sum() | |
| terminated = not (height > 0.8 and height < 2.0 and ang > -1.0 and ang < 1.0) | |
| ob = self._get_obs() | |
| if self.render_mode == "human": | |
| self.render() | |
| return ob, reward, terminated, False, {} | |
| def _get_obs(self): | |
| qpos = self.sim.data.qpos | |
| qvel = self.sim.data.qvel | |
| return np.concatenate([qpos[1:], np.clip(qvel, -10, 10)]).ravel() | |
| def reset_model(self): | |
| self.set_state( | |
| self.init_qpos | |
| + self.np_random.uniform(low=-0.005, high=0.005, size=self.model.nq), | |
| self.init_qvel | |
| + self.np_random.uniform(low=-0.005, high=0.005, size=self.model.nv), | |
| ) | |
| return self._get_obs() | |
| def viewer_setup(self): | |
| assert self.viewer is not None | |
| self.viewer.cam.trackbodyid = 2 | |
| self.viewer.cam.distance = self.model.stat.extent * 0.5 | |
| self.viewer.cam.lookat[2] = 1.15 | |
| self.viewer.cam.elevation = -20 | |