add disable goal & relative goal to tt prodmp
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@ -557,8 +557,8 @@ for _v in _versions:
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kwargs_dict_tt_promp['name'] = _v
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kwargs_dict_tt_promp['controller_kwargs']['p_gains'] = 0.5 * np.array([1.0, 4.0, 2.0, 4.0, 1.0, 4.0, 1.0])
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kwargs_dict_tt_promp['controller_kwargs']['d_gains'] = 0.5 * np.array([0.1, 0.4, 0.2, 0.4, 0.1, 0.4, 0.1])
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kwargs_dict_tt_promp['phase_generator_kwargs']['learn_tau'] = True
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kwargs_dict_tt_promp['phase_generator_kwargs']['learn_delay'] = True
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kwargs_dict_tt_promp['phase_generator_kwargs']['learn_tau'] = False
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kwargs_dict_tt_promp['phase_generator_kwargs']['learn_delay'] = False
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kwargs_dict_tt_promp['phase_generator_kwargs']['tau_bound'] = [0.8, 1.5]
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kwargs_dict_tt_promp['phase_generator_kwargs']['delay_bound'] = [0.05, 0.15]
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kwargs_dict_tt_promp['basis_generator_kwargs']['num_basis'] = 3
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@ -584,7 +584,8 @@ for _v in _versions:
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kwargs_dict_tt_prodmp['controller_kwargs']['p_gains'] = 0.5 * np.array([1.0, 4.0, 2.0, 4.0, 1.0, 4.0, 1.0])
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kwargs_dict_tt_prodmp['controller_kwargs']['d_gains'] = 0.5 * np.array([0.1, 0.4, 0.2, 0.4, 0.1, 0.4, 0.1])
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kwargs_dict_tt_prodmp['trajectory_generator_kwargs']['auto_scale_basis'] = True
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kwargs_dict_tt_prodmp['trajectory_generator_kwargs']['goal_offset'] = 1.0
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kwargs_dict_tt_prodmp['trajectory_generator_kwargs']['relative_goal'] = True
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kwargs_dict_tt_prodmp['trajectory_generator_kwargs']['disable_goal'] = True
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kwargs_dict_tt_prodmp['phase_generator_kwargs']['tau_bound'] = [0.8, 1.5]
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kwargs_dict_tt_prodmp['phase_generator_kwargs']['delay_bound'] = [0.05, 0.15]
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kwargs_dict_tt_prodmp['phase_generator_kwargs']['learn_tau'] = True
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@ -593,8 +594,6 @@ for _v in _versions:
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kwargs_dict_tt_prodmp['basis_generator_kwargs']['alpha'] = 25.
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kwargs_dict_tt_prodmp['basis_generator_kwargs']['basis_bandwidth_factor'] = 3
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kwargs_dict_tt_prodmp['phase_generator_kwargs']['alpha_phase'] = 3
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# kwargs_dict_tt_prodmp['black_box_kwargs']['max_planning_times'] = 3
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# kwargs_dict_tt_prodmp['black_box_kwargs']['replanning_schedule'] = lambda pos, vel, obs, action, t : t % 50 == 0
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register(
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id=_env_id,
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entry_point='fancy_gym.utils.make_env_helpers:make_bb_env_helper',
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@ -7,4 +7,4 @@ def compare_bases_shape(env1_id, env2_id):
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env2.traj_gen.show_scaled_basis(plot=True)
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return
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if __name__ == '__main__':
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compare_bases_shape("BoxPushingDenseReplanProDMP-v0", "BoxPushingDenseProMP-v0")
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compare_bases_shape("TableTennis4DProDMP-v0", "TableTennis4DProMP-v0")
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