Multi-robot formation control: a comparison between model-based and learning-based methods

Abstract

Formation control of multi-robot systems has been extensively studied by model-based methods, where analytic control inputs are constructed based on the kinematics and/or dynamics model and the communication graphs of the multi-robot system. Recently, driven by remarkable advances of robotic learning techniques, emerging studies on learning-based methods for formation control have been developed for adaptive and intelligent control of multi-robot systems. This paper aims to provide a brief overview of our recent development of learning-based formation control, and compare it with a model-based method for a case study of three-robot formation control. Fundamental principles, experimental results and technical challenges are presented, comparing the two different methodologies.