exp: 轮次36——规划起点 r 分布实测，循环内共享 FK(#19) 在部署 r3 口径只值 0.03 ms/次，判掉

ml/sim/closed_loop.py

@@ -197,7 +197,7 @@ def rollout(model, kin, tasks, device, K=8, safety=False, seed=0, max_sec=None,
     # 2026-10-20（轮次33）：速度/加速度按「实际执行位移」算，不看指令——第30轮证明反馈是在限幅之后叠加的
     vratio = torch.zeros(B, device=device); aratio = torch.zeros(B, device=device); prev_exec = torch.zeros(B, 6, device=device)
     traj = [q.clone()] if return_traj else None
-    plans = {k: [] for k in ('it', 'qe', 'commit', 'points', 'midpoints', 'gaps', 'certified')} if return_traj else None
+    plans = {k: [] for k in ('it', 'r', 'qe', 'commit', 'points', 'midpoints', 'gaps', 'certified')} if return_traj else None
     n_start = int(round(0.5 / DT)); moved_start = None          # R2 起步失败：0.5 s 内关节总行程 < 1°
     k2s = int(round(2.0 / DT)); e2 = None
     e0, _ = goal_err(kin, q0, T, R)
@@ -422,6 +422,7 @@ def rollout(model, kin, tasks, device, K=8, safety=False, seed=0, max_sec=None,
             last = torch.cat([qe[:, None], fut[ar, pick]], 1); last_ok = committed; last_brake = braked
             if return_traj:
                 plans['it'].append(it + r)
+                plans['r'].append(r)
                 for key, value in (('qe', qe), ('commit', commit), ('points', cert_pts), ('midpoints', cert_mids), ('gaps', cert_gaps), ('certified', certified)):
                     plans[key].append(value)
             queue = torch.cat([queue, commit], 1)
@@ -476,7 +477,7 @@ def rollout(model, kin, tasks, device, K=8, safety=False, seed=0, max_sec=None,
            'goal_ratio_2s': ratio2.cpu(), 'speed_ratio': vratio.cpu(), 'accel_ratio': aratio.cpu()}
     if return_traj:
         per['traj'] = torch.stack(traj, 1).cpu()
-        per['plans'] = {k: torch.tensor(v) if k == 'it' else torch.stack(v, 1).cpu() for k, v in plans.items()}
+        per['plans'] = {k: torch.tensor(v) if k in ('it', 'r') else torch.stack(v, 1).cpu() for k, v in plans.items()}
     return res, per