fix: smooth APPO Go1 joystick actions

conf/appo/task/go1_joystick_flat/motrix.yaml

@@ -0,0 +1,34 @@
+# @package _global_
+training:
+  task_name: Go1JoystickFlat
+  sim_backend: motrix
+algo:
+  num_envs: 1024
+  steps_per_env: 24
+  max_iterations: 300
+  actor:
+    distribution_cfg:
+      init_std: 0.5
+  algorithm:
+    learning_rate: 5.0e-4
+    entropy_coef: 1.0e-3
+    desired_kl: 0.008
+env:
+  sim_dt: 0.01
+  commands:
+    vel_limit:
+      - [0.5, 0.0, 0.0]
+      - [0.5, 0.0, 0.0]
+reward:
+  scales:
+    tracking_lin_vel: 1.0
+    tracking_ang_vel: 0.2
+    lin_vel_z: -5.0
+    ang_vel_xy: -0.1
+    base_height: -100.0
+    action_rate: -0.015
+    action_smooth: -0.01
+    similar_to_default: -0.15
+    swing_feet_z: 2.0
+  tracking_sigma: 0.25
+  base_height_target: 0.3

docs/sphinx/source/zh_CN/5-reference/5-support_matrix.md

@@ -92,7 +92,7 @@ uv run scripts/generate_support_matrix.py --write
 | PPO (mlx) | `go2w_joystick_flat` (go2w joystick flat) | Configured | Configured |
 | PPO (mlx) | `go2w_joystick_rough` (go2w joystick rough) | Configured | Configured |
 | PPO (mlx) | `stewart_balance` (stewart balance) | Configured | Configured |
-| APPO (torch) | `go1_joystick_flat` (Go1 joystick) | Tested | Registered |
+| APPO (torch) | `go1_joystick_flat` (Go1 joystick) | Tested | Tested |
 | APPO (torch) | `go2_joystick_flat` (Go2 joystick) | Tested | Tested |
 | APPO (torch) | `g1_walk_flat` (G1 walk flat) | Tested | Registered |
 | APPO (torch) | `g1_motion_tracking` (G1 motion tracking) | Tested | Tested |

src/unilab/envs/locomotion/common/rewards.py

@@ -149,6 +149,14 @@ def action_rate(ctx: RewardContext) -> np.ndarray:
     return np.sum(np.square(current - last), axis=1)  # type: ignore[no-any-return]
 
 
+def action_smooth(ctx: RewardContext) -> np.ndarray:
+    """Penalty for second-order action changes between timesteps."""
+    current = ctx.info["current_actions"]
+    last = ctx.info["last_actions"]
+    previous = ctx.info.get("previous_actions", last)
+    return np.sum(np.square(current - 2.0 * last + previous), axis=1)  # type: ignore[no-any-return]
+
+
 # ── effort penalties ─────────────────────────────────────────────────
 
 

src/unilab/envs/locomotion/go1/joystick.py

@@ -142,7 +142,9 @@ def _init_reward_functions(self):
             "ang_vel_xy": rewards.ang_vel_xy,
             "base_height": rewards.base_height,
             "action_rate": rewards.action_rate,
+            "action_smooth": rewards.action_smooth,
             "similar_to_default": rewards.similar_to_default,
+            "contact": self._reward_contact,
             "swing_feet_z": self._reward_swing_feet_z,
         }
 
@@ -239,3 +241,19 @@ def _reward_swing_feet_z(self, ctx: RewardContext) -> np.ndarray:
         swing_rew = np.exp(-height_error / 0.01) * is_swing
         reward: np.ndarray = np.sum(swing_rew, axis=1) / len(self._cfg.sensor.feet_pos)
         return reward
+
+    def apply_action(self, actions: np.ndarray, state: NpEnvState) -> np.ndarray:
+        previous_current = state.info.get("current_actions", np.zeros_like(actions))
+        previous_last = state.info.get("last_actions", np.zeros_like(actions))
+        state.info["previous_actions"] = previous_last
+        state.info["last_actions"] = previous_current
+        state.info["current_actions"] = actions
+        exec_actions = (
+            state.info["last_actions"]
+            if self._cfg.control_config.simulate_action_latency
+            else actions
+        )
+        ctrl: np.ndarray = (
+            exec_actions * self._cfg.control_config.action_scale + self.default_angles
+        )
+        return ctrl

tests/scripts/test_support_matrix.py

@@ -20,11 +20,11 @@ def test_support_matrix_marks_go2_ppo_backends_as_tested():
     assert row.cells["motrix"].level == EvidenceLevel.TESTED
 
 
-def test_support_matrix_marks_appo_go1_motrix_as_registered_only():
+def test_support_matrix_marks_appo_go1_backends_as_tested():
     row = _row("APPO (torch)", "go1_joystick_flat")
 
     assert row.cells["mujoco"].level == EvidenceLevel.TESTED
-    assert row.cells["motrix"].level == EvidenceLevel.REGISTERED
+    assert row.cells["motrix"].level == EvidenceLevel.TESTED
 
 
 def test_support_matrix_keeps_uncovered_mlx_tasks_at_configured():