fix: MuJoCo sim2sim default_angles match MotrixSim training

motrix_rl/src/motrix_rl/rslrl/torch/train/dreamwaq_ppo.py

@@ -222,8 +222,8 @@ class DreamWaQPPO(PPO):
         cv = std_r / (mean_r + 1e-6)
         if not (0 <= cv < 1e6):  # NaN 或 Inf → 保持当前 prob
             return
-        # CV → bootstrap 概率（CV 高→不稳定→多用 GT；上限 0.9 保证 CENet vel head 有梯度）
-        self.actor._adaboot_prob = max(0.0, min(0.9, cv * 5.0))
+        # CV → bootstrap 概率（CENet vel head 通过 VAE loss 已有梯度，无需额外保护）
+        self.actor._adaboot_prob = max(0.0, min(1.0, cv * 5.0))
 
     def _compute_surrogate_loss(
         self, actions_batch, actions_log_prob_batch,

motrix_rl/src/motrix_rl/tasks/go1.py

@@ -136,7 +136,7 @@ class rslrl:
             runner.actor.class_name = (
                 "motrix_rl.rslrl.torch.models.cenet_actor:CENetActorModel")
             runner.actor.hidden_dims = [512, 256, 128]
-            runner.actor.init_noise_std = 0.5  # 与 fixed schedule 配合
+            runner.actor.init_noise_std = 1.0  # 论文原值
 
             # Critic：标准 MLPModel，输入 privileged_obs
             runner.critic.class_name = "MLPModel"

scripts/dreamwaq_sim2sim_mujoco.py

@@ -37,11 +37,12 @@ MAX_VX, MAX_VY, MAX_WZ = 1.0, 1.0, 1.0
 
 # DreamWaQ default joint angles — MUST match MuJoCo XML joint order:
 # qpos[7:19] = FR_hip,FR_thigh,FR_calf, FL_hip,FL_thigh,FL_calf, RR_hip,RR_thigh,RR_calf, RL_hip,RL_thigh,RL_calf
+# 必须与 MotrixSim 训练的 default_angles 完全一致！
 DEFAULT_ANGLES = np.array([
-    -0.1, 0.8, -1.5,   # FR
-    0.1, 0.8, -1.5,     # FL
-    -0.1, 1.0, -1.5,    # RR
-    0.1, 1.0, -1.5,     # RL
+    0.0, 0.9, -1.8,   # FR
+    0.0, 0.9, -1.8,   # FL
+    0.0, 0.9, -1.8,   # RR
+    0.0, 0.9, -1.8,   # RL
 ], dtype=np.float32)