import os from gym import error, spaces from gym.utils import seeding import numpy as np from os import path import gym import six try: import mujoco_py except ImportError as e: raise error.DependencyNotInstalled("{}. (HINT: you need to install mujoco_py, and also perform the setup instructions here: https://github.com/openai/mujoco-py/.)".format(e)) DEFAULT_SIZE = 500 class MujocoEnv(gym.Env): """Superclass for all MuJoCo environments. """ def __init__(self, model_path, frame_skip): if model_path.startswith("/"): fullpath = model_path else: fullpath = os.path.join(os.path.dirname(__file__), "assets", model_path) if not path.exists(fullpath): raise IOError("File %s does not exist" % fullpath) self.frame_skip = frame_skip self.model = mujoco_py.load_model_from_path(fullpath) self.sim = mujoco_py.MjSim(self.model) self.data = self.sim.data self.viewer = None self._viewers = {} self.metadata = { 'render.modes': ['human', 'rgb_array', 'depth_array'], 'video.frames_per_second': int(np.round(1.0 / self.dt)) } self.init_qpos = self.sim.data.qpos.ravel().copy() self.init_qvel = self.sim.data.qvel.ravel().copy() observation, _reward, done, _info = self.step(np.zeros(self.model.nu)) assert not done self.obs_dim = observation.size bounds = self.model.actuator_ctrlrange.copy() low = bounds[:, 0] high = bounds[:, 1] self.action_space = spaces.Box(low=low, high=high, dtype=np.float32) high = np.inf*np.ones(self.obs_dim) low = -high self.observation_space = spaces.Box(low, high) self.seed() def seed(self, seed=None): self.np_random, seed = seeding.np_random(seed) return [seed] # methods to override: # ---------------------------- def reset_model(self): """ Reset the robot degrees of freedom (qpos and qvel). Implement this in each subclass. """ raise NotImplementedError def viewer_setup(self): """ This method is called when the viewer is initialized and after every reset Optionally implement this method, if you need to tinker with camera position and so forth. """ pass # ----------------------------- def reset(self): self.sim.reset() ob = self.reset_model() old_viewer = self.viewer for v in self._viewers.values(): self.viewer = v self.viewer_setup() self.viewer = old_viewer return ob def set_state(self, qpos, qvel): assert qpos.shape == (self.model.nq,) and qvel.shape == (self.model.nv,) old_state = self.sim.get_state() new_state = mujoco_py.MjSimState(old_state.time, qpos, qvel, old_state.act, old_state.udd_state) self.sim.set_state(new_state) self.sim.forward() @property def dt(self): return self.model.opt.timestep * self.frame_skip def do_simulation(self, ctrl, n_frames): self.sim.data.ctrl[:] = ctrl for _ in range(n_frames): self.sim.step() def render(self, mode='human', width=DEFAULT_SIZE, height=DEFAULT_SIZE): if mode == 'rgb_array': self._get_viewer(mode).render(width, height) # window size used for old mujoco-py: data = self._get_viewer(mode).read_pixels(width, height, depth=False) # original image is upside-down, so flip it return data[::-1, :, :] elif mode == 'depth_array': self._get_viewer(mode).render(width, height) # window size used for old mujoco-py: # Extract depth part of the read_pixels() tuple data = self._get_viewer(mode).read_pixels(width, height, depth=True)[1] # original image is upside-down, so flip it return data[::-1, :] elif mode == 'human': self._get_viewer(mode).render() def close(self): if self.viewer is not None: # self.viewer.finish() self.viewer = None self._viewers = {} def _get_viewer(self, mode): self.viewer = self._viewers.get(mode) if self.viewer is None: if mode == 'human': self.viewer = mujoco_py.MjViewer(self.sim) elif mode == 'rgb_array' or mode == 'depth_array': self.viewer = mujoco_py.MjRenderContextOffscreen(self.sim, -1) self.viewer_setup() self._viewers[mode] = self.viewer return self.viewer def get_body_com(self, body_name): return self.data.get_body_xpos(body_name) def state_vector(self): return np.concatenate([ self.sim.data.qpos.flat, self.sim.data.qvel.flat ])