Abstract
Self-localization is one of the most important problems for autonomous mobile robots. We propose a distributed self-localization technique for a herd of mobile robots. The robots' overall positional information in world coordinate system is obtained by an external observer and is shared between the robots. Then, each robot estimates its own position by Bayesian estimation using local odometry data and shared positional information. The authors performed a computer simulation to confirm the basic validity of this algorithm and show its result in this paper.
