This paper presents three methods for anonymous mobile robots localization within a global frame. An aerial camera takes, at regular time intervals, pictures of the area in which robots are moving. The camera determines the coordinates of each robot. Each robot receives the whole set of coordinates extracted from each picture. Mobile Robots are all identical, they do not have any identifier and they can neither communicate with each other nor they can detect themselves. The first localization method is based on the analysis of the angular variation between two images. The second method relies on the analysis of the distances stemmed from three successive pictures. The last one determines if there exists an orientation allowing a specific robot to travel the path between two successive positions. A simulation plateform using augmented reality and the multi-robot software Player-Stage are presented. This plateform is used for validating the different localization methods. Tests and results are presented and compared. CONFIDENTIAL. Limited circulation. For review only.

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.