Information Distributed Kalman Filter Applied to Rendezvous Problems in Cooperative Robotic Teams

Abstract

Rendezvous is a common cooperative task for a team of mobile robots and is widely studied in the literature. The most recent studies suggest distributed approaches to this technique. So, this paper proposes a distributed technique for the robots to achieve rendezvous using the information of their positions even if they have a high level of uncertainty in that. For this, the robots use a Kalman filter in the information form, carried out in a distributed way and using a consensus algorithm to fuse its neighbors’ data. Several simulations were made and the discussion about the results is presented, choosing one particular case to expose more deeply. A comparison is made with a basic consensus algorithm and a predictive controller found in the literature. The results are promising in terms of computational cost, control effort and error in the information about the rendezvous point when dealing with higher levels of uncertainty in the information.