replace joint_pos_limits reward with isaaclabs'; clean code; update readme.

README.md

@@ -182,9 +182,10 @@ xml_path: "{ROOT_DIR}/resources/go2/your-custom-scene.xml"
 
 - Different tracking reward formulation (fixed sigma vs. dynamic sigma)
 - Different rewards:
-  - lower dof_acc_l2 weight in Lab due to physics-step level implementation and sensitivity to outliers
+  - lower joint_acc_l2 weight in Lab due to physics-step level implementation and sensitivity to outliers
   - extra joint_pos_penalty_l1 reward in Lab due to better performance
 - Lack domain_rand: randomize_motor_strength
+- Extra domain_rand: randomize_com_positions_other (lead to better performance)
 
 ---
 

source/robot_lab/robot_lab/tasks/go2/env_cfg.py

@@ -403,10 +403,10 @@ class RewardsCfg:
         weight=-1.0,
         params={"sensor_cfg": SceneEntityCfg("contact_forces", body_names=".*_thigh|.*_calf"), "threshold": 5.0},
     )
-    dof_pos_limits = RewTerm(
+    joint_pos_limits = RewTerm(
-        func=mdp.dof_pos_limits,
+        func=mdp.joint_pos_limits,
         weight=-2.0,
-        params={"asset_cfg": SceneEntityCfg("robot")},
+        params={"asset_cfg": SceneEntityCfg("robot", joint_names=JOINT_NAMES)},
     )
     feet_regulation = RewTerm(
         func=mdp.feet_regulation,

source/robot_lab/robot_lab/tasks/go2/mdp/commands.py

@@ -373,23 +373,8 @@ class Go2RLGymCommandCfg(CommandTermCfg):
         'ang_vel_yaw': [-2.0, 2.0], # min max [rad/s]
     }]
     """List for command range curriculums at specific training iterations"""
-    # terrain_max_command_ranges: dict[str, dict] = {
-    #     'random_rough':
-    #         {'lin_vel_x': [-1.5, 1.5], 'lin_vel_y': [-1.0, 1.0], 'ang_vel_yaw': [-1.5, 1.5]},
-    #     'hf_pyramid_slope':
-    #         {'lin_vel_x': [-1.5, 1.5], 'lin_vel_y': [-1.0, 1.0], 'ang_vel_yaw': [-1.5, 1.5]},
-    #     'hf_pyramid_slope_inv':
-    #         {'lin_vel_x': [-1.5, 1.5], 'lin_vel_y': [-1.0, 1.0], 'ang_vel_yaw': [-1.5, 1.5]},
-    #     'pyramid_stairs':
-    #         {'lin_vel_x': [-1.0, 1.0], 'lin_vel_y': [-1.0, 1.0], 'ang_vel_yaw': [-1.5, 1.5]},
-    #     'pyramid_stairs_inv':
-    #         {'lin_vel_x': [-1.0, 1.0], 'lin_vel_y': [-1.0, 1.0], 'ang_vel_yaw': [-1.5, 1.5]},
-    #     'boxes':
-    #         {'lin_vel_x': [-1.0, 1.0], 'lin_vel_y': [-1.0, 1.0], 'ang_vel_yaw': [-1.5, 1.5]},
-    #     'flat':
-    #         {'lin_vel_x': [-2.0, 2.0], 'lin_vel_y': [-1.0, 1.0], 'ang_vel_yaw': [-2.0, 2.0]},
-    # }
     terrain_max_command_ranges: dict[str, dict] = {
+        #### go2 terrains ####
         'wave':
             {'lin_vel_x': [-1.5, 1.5], 'lin_vel_y': [-1.0, 1.0], 'ang_vel_yaw': [-1.5, 1.5]},
         'slope_up':
@@ -410,6 +395,19 @@ class Go2RLGymCommandCfg(CommandTermCfg):
             {'lin_vel_x': [-1.0, 1.0], 'lin_vel_y': [-1.0, 1.0], 'ang_vel_yaw': [-1.5, 1.5]},
         'flat':
             {'lin_vel_x': [-2.0, 2.0], 'lin_vel_y': [-1.0, 1.0], 'ang_vel_yaw': [-2.0, 2.0]},
+        #### robotlab default terrains ####
+        'random_rough':
+            {'lin_vel_x': [-1.5, 1.5], 'lin_vel_y': [-1.0, 1.0], 'ang_vel_yaw': [-1.5, 1.5]},
+        'hf_pyramid_slope':
+            {'lin_vel_x': [-1.5, 1.5], 'lin_vel_y': [-1.0, 1.0], 'ang_vel_yaw': [-1.5, 1.5]},
+        'hf_pyramid_slope_inv':
+            {'lin_vel_x': [-1.5, 1.5], 'lin_vel_y': [-1.0, 1.0], 'ang_vel_yaw': [-1.5, 1.5]},
+        'pyramid_stairs':
+            {'lin_vel_x': [-1.0, 1.0], 'lin_vel_y': [-1.0, 1.0], 'ang_vel_yaw': [-1.5, 1.5]},
+        'pyramid_stairs_inv':
+            {'lin_vel_x': [-1.0, 1.0], 'lin_vel_y': [-1.0, 1.0], 'ang_vel_yaw': [-1.5, 1.5]},
+        'boxes':
+            {'lin_vel_x': [-1.0, 1.0], 'lin_vel_y': [-1.0, 1.0], 'ang_vel_yaw': [-1.5, 1.5]},     
     }
     resampling_time: float = 5.0
     resampling_time_range: tuple[float, float] = (5.0, 5.0)

source/robot_lab/robot_lab/tasks/go2/mdp/rewards.py

@@ -605,20 +605,3 @@ def feet_regulation(
     reward = (feet_xy_vel_w.pow(2).sum(dim=-1) * torch.exp(-feet_height / (0.025 * base_height_target))).sum(dim=-1)
 
     return reward
-
-def dof_pos_limits(
-    env: ManagerBasedRLEnv,
-    asset_cfg: SceneEntityCfg = SceneEntityCfg("robot"),
-) -> torch.Tensor:
-    asset = env.scene[asset_cfg.name]
-    
-    joint_pos = asset.data.joint_pos
-    joint_limits = asset.data.soft_joint_pos_limits
-
-    lower = joint_limits[..., 0]
-    upper = joint_limits[..., 1]
-
-    out_of_limits = -(joint_pos - lower).clamp(max=0.0)
-    out_of_limits += (joint_pos - upper).clamp(min=0.0)
-
-    return torch.sum(out_of_limits, dim=1)

source/robot_lab/robot_lab/tasks/go2/mdp/terrains.py

@@ -92,7 +92,7 @@ DEFAULT_TERRAIN_CFG = terrain_gen.TerrainGeneratorCfg(
 
 
 # -----------------------------------------------------------------------------
-# Gym-aligned terrain setup
+# Go2 Terrain setup
 # -----------------------------------------------------------------------------
 @height_field_to_mesh
 def wave_terrain(difficulty: float, cfg) -> np.ndarray: