Sliding mode formation control and target tracking for a team of mobile robots using decentralized and distributed Kalman filter

Abstract

In this paper we introduced a theoretical framework for formation control and target tracking for a limited number of mobile robots with partially unknown dynamic models using decentralized and distributed Kalman filter. The mobile robots seek to track a stochastic target while trying to reach a pre-defined formation. Kalman-consensus filter and decentralized Kalman filter is used to infer the received information from mobile robots. This algorithm is successfully applied to track a target with stochastic linear dynamics. Simulation results shows the efficiency of the proposed method.