Adaptive self-configurable robot swarms based on local interactions

Abstract

This paper presents a motion planning framework for a large number of autonomous robots that enables the robots to configure themselves adaptively into an area of an arbitrary geometry. A locally interacting geometric technique provides a unique solution that allows the robots to converge to the uniform distribution by forming an equilateral triangle with their two neighbors. The basic idea underlying the proposed solution is that robots can be thought of as liquid particles that change their relative positions conforming to the shape of the container they occupy. Specifically, it is assumed that robots are not allowed to have the identification number, a pre-determined leader, a common coordinate system, and communication capabilities. Under such minimal conditions, the convergence of the algorithm is mathematically proved and verified through extensive simulations. The results validate the feasibility of applying the algorithm to self-configuration of mobile sensors across the constrained environment.