用摄像头网络远程指挥多机器人协同作业，无需机器人自带导航硬件。
Multi-Robot Planning and Control from CCTV Camera Networks in a Real Warehouse
- 基于摄像头图谱在图像空间分层规划路径
- 四台机器人在30个摄像头覆盖的仓库中完成任务，平均耗时12分钟
- 适合无导航硬件的轻量级机器人团队部署
将移动机器人在环境中的摄像头网络上实现离线控制，为可扩展自主提供了实际路径，将感知与计算从机器人移出。我们将其从单机器人拓展至真实仓库中的多机器人协同，仅通过分布式闭路电视（CCTV）网络和边缘计算驱动多台机器人。系统完全在未标定的像素级拓扑相机图中运行，支持大范围灵活布设。分层规划器为每台机器人选择相机序列，并在其视角间规划图像空间运动，采用优先级后联合策略，将重叠摄像头区域视为独占资源，同一时间仅由一台机器人占用，防止碰撞与死锁。我们在一个含4台机器人、30个摄像头、6条27米长巷道的真实仓库中验证了该方法，报告任务耗时及协调统计结果。据我们所知，这是首个仅依赖外部摄像头网络和离线计算实现多机器人规划与协调的实地演示，机器人未携带任何专用导航硬件。
原文摘要 · Abstract (English)
Off-board control of mobile robots from cameras embedded in the environment offers a practical path to scalable autonomy, moving sensing and compute off the robots. We extend this idea from the single-robot case to coordinated fleets in a real warehouse, driving multiple robots with only a distributed CCTV network and edge compute. The system operates entirely in image space over an uncalibrated, pixel-wise topological camera graph, enabling wide-area operation with flexible camera placement. A hierarchical planner selects a camera sequence per robot and plans its image-space motion through each view, coordinating robots with a prioritised-then-joint strategy and treating overlapping camera regions as shared resources held by one robot at a time to prevent collisions and deadlocks. We validate the approach in a real warehouse with four robots and 30 cameras across six 27 m aisles, reporting mission times and coordination statistics. To our knowledge, this is the first field demonstration of multi-robot planning and coordination using only an external camera network and off-board compute, with robots carrying no task-specific navigation hardware.
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