feat(layout_optimizer): DE optimizer V2 — custom loop, graduated hard constraints, broad phase

Replace scipy differential_evolution with custom DE loop for per-device
crossover, circular θ wrapping, and configurable mutation strategy
(currenttobest1bin default, best1bin as turbo mode).

Key improvements:
- Graduate ALL hard constraints during DE (proportional penalty instead of
  flat inf), giving DE smooth gradient for reachability, min_spacing, etc.
  Binary inf preserved for final pass/fail reporting.
- 2-axis sweep-and-prune AABB broad phase for collision pair pruning
- Multi-seed injection from multiple seeder presets + Gaussian variants
- snap_theta_safe: collision-check after angle snapping, revert on violation
- Weight normalization (100 distance / 60 angle / 5× hard multiplier)
- Constraint priority field (critical/high/normal/low → weight multiplier)
  with LLM intent interpreter setting priority per constraint type
- Final success field now checks user hard constraints in binary mode
- arm_slider added to mock checker reach table (1.07m)

Tests: 202 passed, 24 new tests added (optimizer 7, constraints 6, broad_phase 11)

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

unilabos/layout_optimizer/server.py

@@ -23,6 +23,7 @@ from fastapi.responses import FileResponse, RedirectResponse
 from fastapi.staticfiles import StaticFiles
 from pydantic import BaseModel
 
+from .constraints import DEFAULT_WEIGHT_ANGLE
 from .device_catalog import (
     create_devices_from_list,
     load_devices_from_assets,
@@ -395,9 +396,9 @@ async def run_optimize(request: OptimizeRequest):
     """接收设备列表+约束，返回最优布局方案。"""
     from fastapi import HTTPException
 
-    from .constraints import evaluate_default_hard_constraints
+    from .constraints import evaluate_default_hard_constraints, evaluate_constraints
     from .mock_checkers import MockCollisionChecker
-    from .optimizer import optimize, snap_theta
+    from .optimizer import optimize, snap_theta, snap_theta_safe
     from .seeders import resolve_seeder_params, seed_layout
 
     logger.info(
@@ -456,10 +457,10 @@ async def run_optimize(request: OptimizeRequest):
                 type="soft",
                 rule_name="prefer_orientation_mode",
                 params={"mode": orientation_mode},
-                weight=request.seeder_overrides.get("orientation_weight", 5.0),
+                weight=request.seeder_overrides.get("orientation_weight", DEFAULT_WEIGHT_ANGLE),
             ))
         # prefer_aligned: penalize non-cardinal angles
-        align_weight = request.seeder_overrides.get("align_weight", 2.0)
+        align_weight = request.seeder_overrides.get("align_weight", DEFAULT_WEIGHT_ANGLE)
         if align_weight > 0:
             constraints.append(Constraint(
                 type="soft",
@@ -479,18 +480,27 @@ async def run_optimize(request: OptimizeRequest):
             seed_placements=seed_placements,
             maxiter=request.maxiter,
             seed=request.seed,
+            workflow_edges=request.workflow_edges or None,
         )
         de_ran = True
     else:
         result_placements = seed_placements
 
-    # 5. θ snap post-processing
-    result_placements = snap_theta(result_placements)
+    # 5. θ snap post-processing（碰撞安全：snap 后验证，失败则回退）
+    result_placements = snap_theta_safe(result_placements, devices, lab, checker)
 
     # 6. Evaluate final cost (binary mode for pass/fail reporting)
     final_cost = evaluate_default_hard_constraints(
         devices, result_placements, lab, checker, graduated=False,
     )
+    # 也检查用户硬约束（binary 模式）
+    if constraints and not math.isinf(final_cost):
+        user_hard_cost = evaluate_constraints(
+            devices, result_placements, lab, constraints, checker,
+            graduated=False,
+        )
+        if math.isinf(user_hard_cost):
+            final_cost = math.inf
 
     return OptimizeResponse(
         placements=[