2018-02-26 17:35:07 +01:00
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import os
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import copy
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import numpy as np
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import gym
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from gym import error, spaces
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from gym.utils import seeding
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from gym.envs.robotics import robot_env
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class HandEnv(robot_env.RobotEnv):
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def __init__(self, model_path, n_substeps, initial_qpos, relative_control):
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self.relative_control = relative_control
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super(HandEnv, self).__init__(
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model_path=model_path, n_substeps=n_substeps, n_actions=20,
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initial_qpos=initial_qpos)
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# RobotEnv methods
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# ----------------------------
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def _set_action(self, action):
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assert action.shape == (20,)
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ctrlrange = self.sim.model.actuator_ctrlrange
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actuation_range = (ctrlrange[:, 1] - ctrlrange[:, 0]) / 2.
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if self.relative_control:
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actuation_center = np.zeros_like(action)
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for i in range(self.sim.data.ctrl.shape[0]):
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actuation_center[i] = self.sim.data.get_joint_qpos(
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self.sim.model.actuator_names[i].replace(':A_', ':'))
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for joint_name in ['FF', 'MF', 'RF', 'LF']:
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act_idx = self.sim.model.actuator_name2id(
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'robot0:A_{}J1'.format(joint_name))
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actuation_center[act_idx] += self.sim.data.get_joint_qpos(
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'robot0:{}J0'.format(joint_name))
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else:
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actuation_center = (ctrlrange[:, 1] + ctrlrange[:, 0]) / 2.
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self.sim.data.ctrl[:] = actuation_center + action * actuation_range
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self.sim.data.ctrl[:] = np.clip(self.sim.data.ctrl, ctrlrange[:, 0], ctrlrange[:, 1])
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def _viewer_setup(self):
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body_id = self.sim.model.body_name2id('robot0:palm')
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lookat = self.sim.data.body_xpos[body_id]
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for idx, value in enumerate(lookat):
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self.viewer.cam.lookat[idx] = value
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self.viewer.cam.distance = 0.5
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self.viewer.cam.azimuth = 55.
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self.viewer.cam.elevation = -25.
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2019-02-15 15:55:51 -08:00
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def render(self, mode='human', width=500, height=500):
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return super(HandEnv, self).render(mode, width, height)
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