A collaborative multi-robot localization method without robot identification

Abstract

This paper introduces a method for multi-robot localization which can be applied to more than two robots without identifying each of them individually. The Monte Carlo localization for the single robot case is extended using negative landmark information and shared belief state in addition to perception. A robot perceives a teammate and broadcasts its observation without identifying the teammate, and whenever a robot receives an observation, the observation is processed only if the robot decides that the observation concerns itself. The experiments are based on scenarios where it is impossible for a single robot to localize precisely and the shared information is ambiguous. We demonstrate successful robot identification and localization results in different scenarios. © 2009 Springer Berlin Heidelberg.