基于事件的控制让机器人集群高效穿越狭窄空间
Event-based Reconfiguration Control for Time-varying Formation of Robot Swarms in Narrow Spaces
- 用事件触发机制动态调整集群形态，实时响应环境变化
- 在狭窄通道中成功导航，各项指标优于现有方法
- 适合需要高效集群协作的智能机器人应用场景
本研究提出一种基于事件的重构控制方法，用于引导机器人集群通过峡谷、隧道和走廊等狭窄复杂环境。将机器人集群建模为无向图，每个节点代表可获取环境与邻近机器人状态信息的个体。控制器根据实时数据动态调节理想形态与直线构型之间的差异，融合人工势场设计的行为策略，实现目标导向运动、队形保持、尾随及避障需求。利用李雅普诺夫定理保证了队形控制的稳定性。仿真与对比实验表明，该控制器不仅能成功引导集群穿越狭窄空间，且在成功率、航向一致性、速度、行程时间与能量效率等关键指标上均优于现有方法。软硬件协同测试验证了其在实际场景中的可行性。控制器源码已开源：https://github.com/duynamrcv/erc。
原文摘要 · Abstract (English)
This study proposes an event-based reconfiguration control to navigate a robot swarm through challenging environments with narrow passages such as valleys, tunnels, and corridors. The robot swarm is modeled as an undirected graph, where each node represents a robot capable of collecting real-time data on the environment and the states of other robots in the formation. This data serves as the input for the controller to provide dynamic adjustments between the desired and straight-line configurations. The controller incorporates a set of behaviors, designed using artificial potential fields, to meet the requirements of goal-oriented motion, formation maintenance, tailgating, and collision avoidance. The stability of the formation control is guaranteed via the Lyapunov theorem. Simulation and comparison results show that the proposed controller not only successfully navigates the robot swarm through narrow spaces but also outperforms other established methods in key metrics including the success rate, heading order, speed, travel time, and energy efficiency. Software-in-the-loop tests have also been conducted to validate the controller's applicability in practical scenarios. The source code of the controller is available at https://github.com/duynamrcv/erc.
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