Adaptive self-assembly in swarm robotics through environmental bias

Abstract

A swarm of robots may face challenges in unknown environments where self-assembly is a necessity e.g. crossing difficult areas. When exploring such environments, the self-assembly process has to be triggered only where needed and only for those robots required, leaving other robots to continue exploration. Further, self-assembled robots should dis-assemble when assembled structures are no longer required. Strategies have thus to be learned to trigger self-assembly and dis-assembly so as to meet the needs of the environment. Research has focused on the learning of strategies where all robots of the swarm had to adopt one common strategy: either self-assembly or dis-assembly. The work herein studies how strategies using both self-assembly and dis-assembly can be learned within the same swarm. Further, the effect of the different environments on this challenge is presented.