Heterogeneous Robot Swarms with an Attention Mechanism for Dynamic Target Tracking

Ziqing Zhou, Bo Chen, Chun Ouyang, Xinyang Dong, Siao Liu, Linqiang Hu, Yi Xie, Zhile Zhao, Zhongxue Gan

Abstract: Multirobot collaboration offers significant potential for diverse applications, including tracking and surveillance. In this paper, we introduce an attention mechanism tailored for heterogeneous robot swarms characterized by varied sensing ranges. This mechanism effectively utilizes the swarm's intrinsic characteristics, enabling rapid information transmission and ensuring consistent collective responses to external stimuli. Additionally, we introduce a pigeon-inspired navigation strategy that effectively replaces the traditional obstacle repulsion term by preventing the swarm from becoming trapped in local min-ima and reducing oscillatory behaviors. To validate the efficacy of our algorithm, we have developed an autonomously designed PlusBot swarm platform, which consists of agile vibration-driven miniature robots. Each of them is equipped with its own computing and communication system and is capable of precise closed-loop motion control. This setup meets the requirements for conducting heterogeneous swarm movement experiments in indoor environments. Through comprehensive numerical simulations and real-world experiments, our method has demonstrated exceptional precision and adaptability in tracking dynamic targets. The comparative analysis under-scores the superiority of our approach, particularly in minimizing swarm collisions and ensuring safe navigation in dynamic target-tracking scenarios involving obstacles.