39 lines
1.0 KiB
Python
39 lines
1.0 KiB
Python
from typing import Tuple, Union
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import numpy as np
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from mp_env_api.interface_wrappers.mp_env_wrapper 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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# TODO: @Max Filter observations correctly
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return np.hstack([
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[True] * 7, # Joint Pos
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[True] * 3, # Ball pos
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[True] * 3 # goal pos
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])
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@property
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def start_pos(self):
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return self.self.init_qpos_tt
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@property
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def current_pos(self) -> Union[float, int, np.ndarray, Tuple]:
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return self.sim.data.qpos[:7].copy()
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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.sim.data.qvel[:7].copy()
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@property
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def goal_pos(self):
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# TODO: @Max I think the default value of returning to the start is reasonable here
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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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