Cooperative Joint Estimation and Localization using Mobile Multi-agent Systems: A Minimum Energy Estimator Approach

This paper investigates the problem of joint localization and target tracking using mobile multi-agent networks. We consider the challenge situation that each agent only has partially observation of the target system and also needs to estimate its relative location in order to utilize meaningfully the target observation. Using a minimum-energy filtering approach, we propose optimal distributed filtering algorithms for local state and target state estimation for network agents that utilize local, relative and communicated measurements that can be obtained at general event times. Numerical examples illustrate the performance of the algorithms for the task of estimating the evolution of a gas concentration in a field due to a gas leak using multi-agent systems.