Adaptive Control in Swarm Robotic Systems

Inspired by the collective behavior observed in natural insects, swarm robotics is a new approach in designing control algorithms for a large group of robots performing a certain task. In such robotic systems, an individual robot with only limited capabilities in terms of sensing, computation, and communication can adapt its own behavior so that a desired collective behavior emerges from the local interactions among robots and between robots and the environment. Swarm robotics has been the focus of increased attention recently because of the benefi cial features demonstrated in such systems, such as higher group efficiency, robustness against the failures of individual robots, flexibility to adapt to changes in the environment, and scalability over a wide range of group sizes. In this article we present an adaptive algorithm to regulate the behavior of an individual robot performing collective foraging tasks. Through the interactions between robots, a desired division of labor can be achieved at the group level. Robot groups also demonstrate the ability to improve energy effici ency and its potential robustness in different environments.