import os import copy import numpy as np import gym from gym import error, spaces from gym.utils import seeding from gym.envs.robotics import robot_env class HandEnv(robot_env.RobotEnv): def __init__(self, model_path, n_substeps, initial_qpos, relative_control): self.relative_control = relative_control super(HandEnv, self).__init__( model_path=model_path, n_substeps=n_substeps, n_actions=20, initial_qpos=initial_qpos, ) # RobotEnv methods # ---------------------------- def _set_action(self, action): assert action.shape == (20,) ctrlrange = self.sim.model.actuator_ctrlrange actuation_range = (ctrlrange[:, 1] - ctrlrange[:, 0]) / 2.0 if self.relative_control: actuation_center = np.zeros_like(action) for i in range(self.sim.data.ctrl.shape[0]): actuation_center[i] = self.sim.data.get_joint_qpos( self.sim.model.actuator_names[i].replace(":A_", ":") ) for joint_name in ["FF", "MF", "RF", "LF"]: act_idx = self.sim.model.actuator_name2id( "robot0:A_{}J1".format(joint_name) ) actuation_center[act_idx] += self.sim.data.get_joint_qpos( "robot0:{}J0".format(joint_name) ) else: actuation_center = (ctrlrange[:, 1] + ctrlrange[:, 0]) / 2.0 self.sim.data.ctrl[:] = actuation_center + action * actuation_range self.sim.data.ctrl[:] = np.clip( self.sim.data.ctrl, ctrlrange[:, 0], ctrlrange[:, 1] ) def _viewer_setup(self): body_id = self.sim.model.body_name2id("robot0:palm") lookat = self.sim.data.body_xpos[body_id] for idx, value in enumerate(lookat): self.viewer.cam.lookat[idx] = value self.viewer.cam.distance = 0.5 self.viewer.cam.azimuth = 55.0 self.viewer.cam.elevation = -25.0 def render(self, mode="human", width=500, height=500): return super(HandEnv, self).render(mode, width, height)