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| import numpy as np | |
| from gym import utils | |
| from gym.envs.mujoco import MuJocoPyEnv | |
| from gym.spaces import Box | |
| class HopperEnv(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=(11,), dtype=np.float64) | |
| MuJocoPyEnv.__init__( | |
| self, "hopper.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() | |
| s = self.state_vector() | |
| terminated = not ( | |
| np.isfinite(s).all() | |
| and (np.abs(s[2:]) < 100).all() | |
| and (height > 0.7) | |
| and (abs(ang) < 0.2) | |
| ) | |
| ob = self._get_obs() | |
| if self.render_mode == "human": | |
| self.render() | |
| return ob, reward, terminated, False, {} | |
| def _get_obs(self): | |
| return np.concatenate( | |
| [self.sim.data.qpos.flat[1:], np.clip(self.sim.data.qvel.flat, -10, 10)] | |
| ) | |
| def reset_model(self): | |
| qpos = self.init_qpos + self.np_random.uniform( | |
| low=-0.005, high=0.005, size=self.model.nq | |
| ) | |
| qvel = self.init_qvel + self.np_random.uniform( | |
| low=-0.005, high=0.005, size=self.model.nv | |
| ) | |
| self.set_state(qpos, qvel) | |
| 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 * 0.75 | |
| self.viewer.cam.lookat[2] = 1.15 | |
| self.viewer.cam.elevation = -20 | |