Experimental and Simulation Platforms for Anonymous Robots Self-Localization

This paper presents an experimental platform and a simulation-based one for the implementation of a method enabling mobile anonymous robots self-localization. The proposed method, theoretically validated in a previous work, is based on the comparison between global information obtained through periodical aerial pictures and local information stemmed from odometry. The process analyzes robots' coordinates evolution between two consecutive pictures and compares these changes with odometric measures. On each picture, robots are anonymous and their identification is impossible without extra information. In this work, measures obtained with actual robots on the experimental platform are compared with the ones obtained on the simulation-based platform reproducing experimental conditions. We show that success rates, defined as the percentage of time robots successfully localize themselves, obtained on both platforms are qualitatively similar while quantitatively different in regard with algorithm performances. Sources responsible for this gap are identified and analyzed. It leads to the conclusion that, in the context of our study, using a simulation-based platform is a valid alternative to actual robots experiments.