ABSTRACT

Distributed localization aims to solve the coordinate of each vehicle in a network in a distributed manner, given the coordinates of a small set of vehicles as the anchors and local inter-vehicle measurements. This chapter presents several results on distributed localization for multi-vehicle networks by using graph Laplacian technique, which is a linear approach and thus ensures global convergence. It establishes a linear constraint on each individual vehicle by using either real barycentric coordinate or complex barycentric coordinate. Centralized localization algorithms collect all inter-vehicle measurements and the known Euclidean coordinates of a small number of vehicles in the network at a computing center and then compute every vehicle's location. For a multi-vehicle network, if the range information is measured by the vehicles according to the sensing graph, then the distributed localization problem becomes the one using range information.