Tune DreamWaQ gait rewards
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@@ -124,8 +124,8 @@ class DreamWaQCfg(Go1WalkNpEnvCfg):
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"ang_vel_xy": -0.10, # 抑制晃动
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"ang_vel_xy": -0.10, # 抑制晃动
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"orientation": -0.5, # 强制平稳姿态
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"orientation": -0.5, # 强制平稳姿态
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"dof_acc": -2.5e-7,
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"dof_acc": -2.5e-7,
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"base_height": -10.0, # 强惩罚身高偏差,避免蹲伏或踮脚
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"base_height": -5.0,
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"feet_air_time": 0.1,
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"feet_air_time": 0.03,
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"action_rate": -0.01,
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"action_rate": -0.01,
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"joint_power": -2e-5,
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"joint_power": -2e-5,
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"smoothness": -0.02,
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"smoothness": -0.02,
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@@ -768,7 +768,7 @@ class DreamWaQTask(Go1WalkTask):
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air_time = info.get("air_time_at_contact")
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air_time = info.get("air_time_at_contact")
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if first_contact is None or air_time is None:
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if first_contact is None or air_time is None:
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return np.zeros(self._num_envs, dtype=np.float32)
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return np.zeros(self._num_envs, dtype=np.float32)
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rew = np.sum((air_time - 0.5) * first_contact, axis=1)
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rew = np.sum(np.maximum(air_time - 0.25, 0.0) * first_contact, axis=1)
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rew *= np.linalg.norm(commands[:, :2], axis=1) > 0.1
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rew *= np.linalg.norm(commands[:, :2], axis=1) > 0.1
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return rew
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return rew
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