Robust multi-robot object localization using fuzzy logic

Cooperative localization of objects is an important challenge in multi-robot systems. We propose a new approach to this problem where we see each robot as an expert which shares unreliable information about object locations. The information provided by different robots is then combined using fuzzy logic techniques, in order to reach a consensus between the robots. This contrasts with most current probabilistic techniques, which average information from different robots in order to obtain a tradeoff, and can thus incur well-known problems when information is unreliable. In addition, our approach does not assume that the robots have accurate self-localization. Instead, uncertainty in the pose of the sensing robot is propagated to object position estimates. We present experimental results obtained on a team of Sony AIBO robots, where we share information about the location of the ball in the RoboCup domain.