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import numpy as np
import gym
from gym.envs.mujoco.ant import AntEnv
from gym.envs.mujoco.humanoid import HumanoidEnv
def gym_env_register(id, max_episode_steps=1000):
def register(gym_env):
spec = {
'id': id,
'entry_point': (f'dizoo.mujoco.envs.mujoco_gym_env:{gym_env.__name__}'),
'max_episode_steps': max_episode_steps
}
gym.register(**spec)
return gym_env
return register
@gym_env_register('AntTruncatedObs-v2')
class AntTruncatedObsEnv(AntEnv):
"""
Overview:
Modified ant with observation dim truncated to 27, which is used in MBPO (arXiv: 1906.08253).
.. note::
External forces (sim.data.cfrc_ext) are removed from the observation.
Otherwise identical to Ant-v2 from\
<https://github.com/openai/gym/blob/master/gym/envs/mujoco/ant.py>.
"""
def _get_obs(self):
return np.concatenate(
[
self.sim.data.qpos.flat[2:],
self.sim.data.qvel.flat,
# np.clip(self.sim.data.cfrc_ext, -1, 1).flat,
]
)
@gym_env_register('HumanoidTruncatedObs-v2')
class HumanoidTruncatedObsEnv(HumanoidEnv):
"""
Overview:
Modified humanoid with observation dim truncated to 45, which is used in MBPO (arXiv: 1906.08253).
.. note::
COM inertia (cinert), COM velocity (cvel), actuator forces (qfrc_actuator),\
and external forces (cfrc_ext) are removed from the observation.
Otherwise identical to Humanoid-v2 from\
<https://github.com/openai/gym/blob/master/gym/envs/mujoco/humanoid.py>.
"""
def _get_obs(self):
data = self.sim.data
return np.concatenate(
[
data.qpos.flat[2:],
data.qvel.flat,
# data.cinert.flat,
# data.cvel.flat,
# data.qfrc_actuator.flat,
# data.cfrc_ext.flat
]
)
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