Multisensor detection schemes for mobile robots
Amir Abbas Fatemi, H. Lecocq · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1996
In this work, mobile robot distributed detection systems are described that use multiple sources of information to construct an internal representation of its environment. We begin by considering a decision fusion model employing the parallel fusion topology. Based on their observations, local sensors make local binary decisions and transmit them to the decision fusion center where they are combined to yield the global decision. Decisions rules are obtained by using different probabilistic methods. The optimal decision scheme at the fusion center is derived, by optimizing three criterions: the mean square error, the maximum a posterior error, and the Bayesian risk. We, then, consider an optimal data fusion where the local decisions are simply added. Finally, an application to the fusion of ultrasound sonar data is presented and discussed.