Multi-Robot Systems

Multi-robot coordinated fencing, where a team of robots forms a protective formation around a target, has garnered significant attention and proven useful in practical applications such as area convoying. However, real-world scenarios often involve complex target characteristics, including varying dynamics and multiple targets, which can pose challenges in maintaining the formation. Additionally, due to sensor costs and environmental constraints, robots may only have access to directional constraint information, presenting further challenges.

This book highlights cooperative fencing approaches for multi-robot systems and their practical applications to different unmanned surface (ground) vehicles, providing an overview of research trends and future directions in coordinated fencing. Firstly, a basic fencing controller using neighboring angle repulsion for a constant-velocity target is designed, laying the groundwork for complex fencing missions. Then, for more complex fencing with an evenly rotating formation, a distributed controller is developed using input-to-state stability, achieving coordinated fencing under intermittently varying topologies. For more complex varying-velocity targets, a distributed fencing controller based on output regulation theory is proposed. For general target fencing missions in both 2D and 3D, a formal long-term task execution framework is developed using control barrier functions. Moreover, unlike previous methods that rely on the relative position between the robot and the target, a distributed bearing-only fencing control algorithm based on the persistent-excitation condition is developed, requiring only comparatively inexpensive sensors. Finally, this exploration into the theory and application of coordinated fencing control provides guidelines for robust, efficient, and complex practical implementations of multi-robot missions.

Highlights cooperative fencing control approaches of multi-robot systems Studies the basic and complex fencing for single-target and multi-target scenarios Presents applications to unmanned vehicles, but also rigorous mathematical results

Autorentext

Bin-Bin Hu obtained the Ph.D. degree in control science and engineering from Huazhong University of Science and Technology, Wuhan, China, in 2022. From August 2022 to August 2024, he was Research Fellow with the School of Mechanical and Aerospace Engineering, at Nanyang Technological University, Singapore. Currently, he is Post-Doctoral Fellow with the University of Groningen, Groningen, the Netherlands. He has published more than 20 peer-reviewed journal and conference papers in the robotics and automatic control fields, including IEEE Transactions on Robotics, IEEE Transactions on Automatic Control, Automatica, etc. He was the recipient of the excellent doctoral dissertation award of the Chinese Association of Automation in 2023. His research interests include control of networked systems, multi-robot systems, and autonomous navigation.

Hai-Tao Zhang received the B.E. and Ph.D. degrees from the University of Science and Technology of China, Hefei, China, in 2000 and 2005, respectively. During January to December 2007, he was Postdoctoral Researcher with the University of Cambridge, Cambridge, UK. Currently, he is Full Professor with Huazhong University of Science and Technology, Wuhan, China. His research interests include swarming intelligence, model predictive control, and unmanned system cooperation control. He is a Cheung Kong Young Scholar. He is/was an associate editor of IEEE Transactions on Systems, Man and Cybernetics-Systems, IEEE Transactions on Circuits and Systems II and Asian Journal of Control.

Inhalt

Introduction to Coordinated Multi-Robot Fencing Control.- Distributed Fencing Control via Neighboring Angle Repulsion.- Distributed Fencing Control Via Input-To-State Stability.- Distributed Fencing Control via Ouput Regulation Theory.- Distributed Fencing Control via Long-Term Task Execution.- Coordinated Multiple-Target Fencing Control and Collision Avoidance.- Coordinated Multiple-Scattered-Targets Fencing via Flexible Subgrouping and Ordering.- Bearing-Only Fencing via Persistent-Exciting Condition.- Summary and Future Work.