Cooperative opinion pool: a new method for sensor fusion by a robot team

Abstract

In this work we overview two popular algorithms for sensor fusion, linear opinion pool (LOP) and logarithmic opinion pool (LGP) and introduce a new method to overcome their difficulties: cooperative opinion pool (COP). COP considers all of the dependencies between observations such as LOP and reduces the uncertainty such as LGP. We check its performance on a simulated multi-robot environment, where a group of robots cooperate to reduce uncertainty of self- localization and object localization. Simulation results show that the entropy of cooperative localization is reduced as the number of cooperating robots grows.