分层协同调度与控制，让工业机器人车队高效避障运行
Combining High Level Scheduling and Low Level Control to Manage Fleets of Mobile Robots
- 高层用ComSat算法生成带时间参数的路径，低层用分布式MPC实时调整轨迹
- 在拥堵场景下仍保持高任务完成率，支持故障或环境变化下的快速重调度
- 模块化设计适合复杂工厂部署，兼顾效率与鲁棒性
工业环境中大规模移动机器人进行物料搬运需要在动态场景中实现可扩展的协调。本文提出一种两层框架，结合高层调度与低层控制：使用组合算法ComSat为每台机器人生成带时间参数的路径；这些调度结果由分布式模型预测控制（MPC）系统实时利用，计算局部参考轨迹，应对静态和动态障碍物。该方法确保安全无碰撞运行，并可在机器人故障或环境变化时快速重新调度。我们在不同道路容量和交通条件的二维仿真环境中评估该方法，结果显示即使在拥堵情况下仍具备高任务完成率和强鲁棒性。框架的模块化结构保证了计算可行性与灵活性，适用于复杂的真实工业场景。
原文摘要 · Abstract (English)
The deployment of mobile robots for material handling in industrial environments requires scalable coordination of large fleets in dynamic settings. This paper presents a two-layer framework that combines high-level scheduling with low-level control. Tasks are assigned and scheduled using the compositional algorithm ComSat, which generates time-parameterized routes for each robot. These schedules are then used by a distributed Model Predictive Control (MPC) system in real time to compute local reference trajectories, accounting for static and dynamic obstacles. The approach ensures safe, collision-free operation, and supports rapid rescheduling in response to disruptions such as robot failures or environmental changes. We evaluate the method in simulated 2D environments with varying road capacities and traffic conditions, demonstrating high task completion rates and robust behavior even under congestion. The modular structure of the framework allows for computational tractability and flexibility, making it suitable for deployment in complex, real-world industrial scenarios.
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