【量子×DRL物流最適化 #13】ROS 2・倉庫ロボット協調制御

制約：各タスクは必ず1台に割り当て

    for t_idx in range(n_tasks):
        for r1 in range(n_robots):
            idx1 = var(r1, t_idx)
            Q[(idx1, idx1)] = Q.get((idx1, idx1), 0) - lambda_penalty
            for r2 in range(r1+1, n_robots):
                idx2 = var(r2, t_idx)
                Q[(idx1, idx2)] = Q.get((idx1, idx2), 0) + 2 * lambda_penalty

    bqm = dimod.BinaryQuadraticModel.from_qubo(Q)
    sampler = SimulatedAnnealingSampler()
    sampleset = sampler.sample(bqm, num_reads=1000)

    # 解をデコード
    best = sampleset.first.sample
    assignment = {rid: [] for rid in robots}

    for r_idx, rid in enumerate(robots):
        for t_idx, task in enumerate(tasks):
            if best.get(var(r_idx, t_idx), 0) == 1:
                assignment[rid].append(task)

    return assignment

async def send_to_charging_station(self, robot_id: str):
    """ロボットを充電ステーションに誘導"""
    charging_station = (0.0, 0.0)  # 充電ステーション座標

    # ROS 2 Action: NavigateThroughPoses
    # 実際の実装ではrclpyを使用
    print(f"🔋 {robot_id}を充電ステーションへ誘導: {charging_station}")

async def warehouse_simulation():
robot_ids = [f"AMR_{i:03d}" for i in range(5)]
coordinator = WarehouseRobotCoordinator(robot_ids)

for i, rid in enumerate(robot_ids):
    state = RobotState(
        robot_id=rid, x=float(i * 5), y=0.0, theta=0.0,
        battery_pct=85.0 + i * 2, payload_kg=0.0, status='idle'
    )
    await coordinator.update_robot_state(rid, state)

picking_tasks = []
for i in range(12):
    task = type('PickingTask', (), {
        'task_id': f'PICK_{i:04d}',
        'pickup_location': (float(i*4), float(i*3)),
        'priority': (i % 3) + 1,
        'weight_kg': float(i + 1)
    })()
    picking_tasks.append(task)

assignment = await coordinator.assign_optimal_tasks(picking_tasks)

print("\n📋 タスク割り当て結果:")
for robot_id, tasks in assignment.items():
    task_ids = [getattr(t, 'task_id', '?') for t in tasks]
    print(f"  {robot_id}: {len(tasks)}件")

total_assigned = sum(len(v) for v in assignment.values())
print(f"\n✅ 合計 {total_assigned}/{len(picking_tasks)} 件を割り当て完了")

if name == "main":
import numpy as np
asyncio.run(warehouse_simulation())

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## 6. 性能評価と産業実装の考察

### 6.1 ベンチマーク結果（実測値）