Decentralized range-based linear motion estimation in acyclic vehicle formations with fixed topologies

Abstract

The problem of decentralized state estimation in formations of autonomous vehicles is addressed in this paper. A reduced number of agents in the formation have access to absolute position measurements, while the rest must rely on range measurements to neighboring agents and local sensing and communication capabilities to estimate their own position and velocity. A method for designing local state estimators for each of the agents is presented such that the resulting decentralized state estimator features globally exponentially stable error dynamics when the graph associated with the formation is acyclic. Realistic simulation results are presented and discussed to assess the performance of the proposed solution under the influence of measurement noise.