Swarm Robotics in Adversarial Scenarios

Abstract

Swarm robotics takes inspiration from the collective behaviour observed in nature in many living species, where local interactions between individuals and with the environment lead a group of autonomous agents to solve complex tasks in a distributed manner, without a central control unit. It is a field of research that studies how systems composed of multiple autonomous agents (robots) can be used to accomplish collective tasks, where the tasks either cannot be accomplished by each individual robot alone, or are carried out more effectively by the robots as a group. In this talk, work addressing interesting problems in swarm robotics that deployed in adversarial scenarios, including pursuit-evasion, defence-intrusion, multi-target trapping, and shepherding will be described. Dr Zhang will also show how collective behaviours of natural species become good inspirations for the design of distributed methods in real swarm robotic systems (e.g., drone swarm).

Speaker

Dr Shuai Zhang is a Postdoctoral Fellow at the Centre for Garment Production limited, HK. He is also a Research Associate at the Department of Computer Science, The University of Hong Kong. Dr Zhang holds a BSc degree in Robotics and Autonomous System, a MSc degree in Weapon Systems and Utilization, and a PhD degree in Armament Science and Technology. He held joint PhD position at the Department of Mechanical & Aerospace Engineering, University of Strathclyde, UK. His research interests are swarm intelligence, collective behaviour, and swarm robotics. Currently, his research is focusing on designing distributed methods for swarm robots to accomplish complex tasks that are involved in adversarial scenarios. Dr Zhang has published a list of peer-reviewed articles on robotics and autonomous systems, swarm robotics, and evolutionary game theory. He served as a reviewer in several journals, including Scientific Reports, Journal of Physics: complexity, SN Applied Sciences, The IEEE Transactions on Control of Network Systems, Nonlinear Dynamics, and International Journal of Power Electronics and Drive System.