Normalize with median new-calibration SO-101 dataset stats; sim joints in LeRobot degrees directly

app.py

@@ -60,7 +60,20 @@ CAM_W, CAM_H = 320, 240
 VIDEO_W, VIDEO_H = 480, 360
 VIDEO_STRIDE = 2
 
+NORMALIZATION = {
+    "state": {
+        "q01": [-37.969, -99.316, -45.78, 22.987, -68.712, 0.45],
+        "q99": [35.288, 43.076, 90.308, 95.704, 17.753, 40.324],
+    },
+    "action": {
+        "q01": [-1.652, -3.235, -3.147, -2.198, -1.708, 0.0],
+        "q99": [1.701, 3.487, 3.307, 2.072, 1.699, 40.733],
+    },
+}
+
 policy = load_policy(REPO).to("cuda")
+policy.config.state_normalization = NORMALIZATION["state"]
+policy.config.action_normalization = NORMALIZATION["action"]
 SNAPSHOTS = [0, N_OBS - 1]
 
 MESH_MANIFEST = viewer.export_meshes(sim.build_model(next(iter(sim.SCENES))))
@@ -146,7 +159,7 @@ def rollout_gpu(prompt, scene, n_chunks, seed, make_video):
         r0 = time.perf_counter()
         cams = (env.render("scene"), env.render("wrist")) if _needs_cams(tick) else (None, None)
         stats["cam_render"] += time.perf_counter() - r0
-        state = sim.lerobot_to_model(env.state_deg())
+        state = env.state_deg()
         command = state if last_command is None else last_command
         entry = (cams[0], cams[1], state, command)
         for _ in range(N_OBS if not history else 1):
@@ -161,7 +174,7 @@ def rollout_gpu(prompt, scene, n_chunks, seed, make_video):
         action = np.asarray(chunk[tick % N_EXEC], dtype=np.float64)
         last_command = action
         p0 = time.perf_counter()
-        env.step(sim.model_to_lerobot(action))
+        env.step(action)
         stats["physics"] += time.perf_counter() - p0
         q0 = time.perf_counter()
         poses.append(viewer.body_poses(env.data, bodies))

sim.py

@@ -139,18 +139,6 @@ def q_to_deg(q):
     return np.concatenate([deg, [g]])
 
 
-MODEL_SIGN = np.array([1.0, -1.0, 1.0, 1.0, 1.0, 1.0])
-MODEL_OFFSET = np.array([0.0, 90.0, 90.0, 0.0, -90.0, 0.0])
-
-
-def lerobot_to_model(deg, sign=MODEL_SIGN, offset=MODEL_OFFSET):
-    return np.asarray(deg, dtype=np.float64) * sign + offset
-
-
-def model_to_lerobot(val, sign=MODEL_SIGN, offset=MODEL_OFFSET):
-    return (np.asarray(val, dtype=np.float64) - offset) / sign
-
-
 @dataclass
 class Sim:
     scene: str = "Cubes and tray"