Swarm Behavioral Sorting based on Robotic Hardware Variation

Abstract

Swarm robotic systems can offer advantages of robustness, flexibility and scalability, just like social insects. One of the issues that researchers are facing is the hardware variation when implementing real robotic swarms. Identical software cannot guarantee identical behaviors among all robots due to hardware differences between swarm members. We propose a novel approach for sorting swarm robots according to their hardware differences. This method is based on the large number of interactions between robots and the environment. Individual robot’s unique hardware circumstance determines its unique decision and reaction during each robotic controlling step, and these unique local reactions accumulate and contribute to the robot’s global behavior. Accordingly by separating these hardware-triggered global behaviors, swarm robots can be sorted according to their hardware variations.