Distributed State Estimation for Multi-Agent with Coupled Distance Constraints

The existing research on distributed constrainted state estimation for multi-agent has predominantly focused on linear equality constraints, thus limiting its practical applications. This paper proposes a novel distributed estimator with coupled distance constraints for multi-agent system. The problem is first reformulated in consensus optimization form, to which the alternating direction method of multipliers can be applied. By adding penalty terms to smooth the state estimates of neighboring agents, the coupled nonlinear constraints are solved interactively. Finally, a simulation of formation vehicles motion is conducted to demonstrate the effectiveness of the proposed algorithm.