A Minimum Energy Filter for Distributed Multirobot Localisation
Abstract
We present a new approach to the cooperative localisation problem by applying the theory of minimum energy filtering. We consider the problem of estimating the pose of a group of mobile robots in an environment where robots can perceive fixed landmarks and neighbouring robots as well as share information with others over a communication channel. Whereas the vast majority of the existing literature applies some variant of a Kalman Filter, we derive a set of filter equations for the global state estimate based on the principle of minimum energy filtering. We show how the filter equations can be decoupled and the calculations distributed among the robots in the network without requiring a central processing node. Finally, we provide a demonstration of the filter's performance in simulation.
Cite
@article{arxiv.2005.07303,
title = {A Minimum Energy Filter for Distributed Multirobot Localisation},
author = {Jack Henderson and Jochen Trumpf and Mohammad Zamani},
journal= {arXiv preprint arXiv:2005.07303},
year = {2021}
}
Comments
To be published at 21st IFAC World Congress, Berlin, Germany, July 12-17, 2020