多机器人协同感知与导航，实现高效无冲突自主协作。
Nav-SCOPE: Swarm Robot Cooperative Perception and Coordinated Navigation
- 通过交互场共享信息，降低环境不确定性
- 路径优化实现自组织协调，收敛快且防碰撞
- 轻量级设计，适合实际部署，计算通信开销小
本文提出一种轻量级的多机器人协同导航系统，采用去中心化协同感知。首先构建信息流，在不可靠自组网络中实现实时观测共享；其次通过交互场传递互补信息，降低各机器人的环境不确定性；最后实现路径优化，支持自组织协调，具备良好收敛性、发散性及避碰能力。方法完全可解释，无需额外开发即可部署。大量仿真与真实实验表明，该方法显著减少路径冗余，适用于多种任务，计算与通信开销极低。
原文摘要 · Abstract (English)
This paper proposes a lightweight systematic solution for multi-robot coordinated navigation with decentralized cooperative perception. An information flow is first created to facilitate real-time observation sharing over unreliable ad-hoc networks. Then, the environmental uncertainties of each robot are reduced by interaction fields that deliver complementary information. Finally, path optimization is achieved, enabling self-organized coordination with effective convergence, divergence, and collision avoidance. Our method is fully interpretable and ready for deployment without gaps. Comprehensive simulations and real-world experiments demonstrate reduced path redundancy, robust performance across various tasks, and minimal demands on computation and communication.
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