Multi-Robot Collaborative Hunting in Cluttered Environments With Obstacle-Avoiding Voronoi Cells  

作　　者：Meng Zhou Zihao Wang Jing Wang Zhengcai Cao 

机构地区：[1]the School of Electrical and Control Engineering,North China University of Technology,Beijing 100144,China [2]IEEE [3]the College of Information Science and Technology,Beijing University of Chemical Technology,Beijing 100029,China

出　　处：《IEEE/CAA Journal of Automatica Sinica》2024年第7期1643-1655,共13页自动化学报（英文版）

基　　金：supported by the National Natural Science Foundation of China (62273007,61973023);Project of Cultivation for Young Top-motch Talents of Beijing Municipal Institutions (BPHR202203032)。

摘　　要：This work proposes an online collaborative hunting strategy for multi-robot systems based on obstacle-avoiding Voronoi cells in a complex dynamic environment. This involves firstly designing the construction method using a support vector machine(SVM) based on the definition of buffered Voronoi cells(BVCs). Based on the safe collision-free region of the robots, the boundary weights between the robots and the obstacles are dynamically updated such that the robots are tangent to the buffered Voronoi safety areas without intersecting with the obstacles. Then, the robots are controlled to move within their own buffered Voronoi safety area to achieve collision-avoidance with other robots and obstacles. The next step involves proposing a hunting method that optimizes collaboration between the pursuers and evaders. Some hunting points are generated and distributed evenly around a circle. Next, the pursuers are assigned to match the optimal points based on the Hungarian algorithm.Then, a hunting controller is designed to improve the containment capability and minimize containment time based on collision risk. Finally, simulation results have demonstrated that the proposed cooperative hunting method is more competitive in terms of time and travel distance.

关 键 词：Dynamic obstacle avoidance multi-robot collaborative hunting obstacle-avoiding Voronoi cells task allocation 

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置]