动态环境下群体机器人协同目标接力追踪控制研究

Cooperative tracking control of swarm robots is the fundamental for applications like cooperative convoy, target monitoring and tracking in specific areas. Currently, there have been numerous research results on swarm approach for multi robot systems with fixed/switching topologies and communication time delays. However, most of these results are under a common assumption that the tracking robots are the same during the whole tracking process. The replacement of robots and change of robots’ number are not considered. This project investigates the relay tracking control strategy under dynamic environment and mainly focuses on the following aspects. 1) An active compensation method based on predictive control will be proposed for relay tracking control of swarm robots with communication time delays. The criterion for determining boundaries of dynamic Voronoi cells will be optimized and the relay tracking strategy will be improved. 2) In order to enhance system’s control performance under time delays, the design method of cooperative relay tracking controller parameters will be developed based on affine Bessel–Legendre inequality. 3) The relay tracking system under the coupling effect of delays and variable numbers will be explored. By constructing a novel average type Lyapunov function and combining the switched delay system theory, the relation between stability and change frequency of numbers of robots is expected to be presented. Cooperative control of swarm robots is a cutting-edge topic in robotics. This project aims to promote the swarm intelligence theory, and provide theoretic solutions for practical applications.

群体机器人协同控制是解决协同护航和无人区域监控与追踪入侵目标等实际问题的重要理论基础。相关研究成果主要针对拓扑结构切换和通信时滞条件下固定机器人追踪系统，未考虑机器人接力替换及数量变化造成的影响。本项目深入开展动态环境下群体机器人接力替换追踪的研究，具体内容：1）拟采用预测控制主动补偿方法处理通信时滞下Voronoi动态图边界确定问题，优化机器人协同接力替换策略；2）提出融合仿射Bessel-Legendre不等式的机器人目标接力追踪分布式控制器参数设计方法，提升时滞群体机器人协同接力追踪性能；3）针对通信时滞和数量时变耦合动态环境下的接力追踪系统，构建新型平均误差Lyapunov函数，结合时滞切换系统分析方法，确定其稳定性条件和可容许的数量时变频率。本项目紧密围绕群体机器人协同控制这一机器人领域前沿性课题，具有理论前瞻性和实际应用前景。

群体智能机器人系统在灾难救援、智能交通、环境探测等领域有着十分广泛的应用前景。本项目紧密围绕群体机器人协同控制技术这一前沿课题，主要研究了基于Voronoi图的群体机器人协同目标接力追踪系统在实际应用中所处的动态环境变化问题。揭示了通信时滞和数量时变的动态环境对群体机器人协同目标接力追踪性能和稳定性的影响机理。提出了基于分布式预测控制的网络时滞环境下Voronoi动态图边界确定主动补偿方法，实现时滞追踪机器人的精确接力控制，得到系统可容许的时滞上界。完善了时滞与数量时变耦合动态环境下接力追踪系统稳定性分析理论体系，实现了群体机器人对目标的快速追踪。在此基础上，探索了异构机器人目标追踪，以及基于深度强化学习的切换拓扑下群体机器人目标追踪拦截问题。研究成果丰富和完善了机器人协同控制的基本理论和研究方法，是有效解决机器人集群护航任务、无人区域入侵目标监控与追踪等实际问题的关键技术，为协同移动目标追踪系统的推广应用起到重要作用。目前已发表相关论文10篇，其中该项目第一标注SCI论文8篇，出版第一标注学术专著1部，授权发明专利1项，登记软件著作权2项。