39 lines
1.2 KiB
Python
39 lines
1.2 KiB
Python
from typing import Tuple, Union
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import numpy as np
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from mp_env_api import MPEnvWrapper
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class MPWrapper(MPEnvWrapper):
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@property
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def active_obs(self):
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# Joint and target positions are randomized, velocities are always set to 0.
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return np.hstack([
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[True] * 3, # target position
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[True] * 12, # sin/cos arm joint position
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[True] * 6, # arm joint torques
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[False] * 6, # arm joint velocities
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[True] * 3, # sin/cos hand joint position
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[False] * 3, # hand joint velocities
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[True] * 3, # hand pinch site position
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[True] * 9, # pinch site rmat
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])
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@property
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def current_pos(self) -> Union[float, int, np.ndarray]:
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return self.env.physics.named.data.qpos[:]
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@property
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def current_vel(self) -> Union[float, int, np.ndarray, Tuple]:
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return self.env.physics.named.data.qvel[:]
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@property
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def goal_pos(self) -> Union[float, int, np.ndarray, Tuple]:
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raise ValueError("Goal position is not available and has to be learnt based on the environment.")
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@property
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def dt(self) -> Union[float, int]:
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return self.env.dt
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