On the Distributed Multi-robot Herding

Eduardo Sebastián, Eduardo Montijano, Carlos Sagüés

Keywords: distributed estimation, graph algorithms, multi-robot systems, nonlinear control

TL;DR: This work addresses the multi-robot herding problem by developing a distributed estimation and control algorithm

Abstract: Multi-robot herding deals with the problem of steering a group of non-cooperative entities towards desired locations by means of a team of robots. Herding demands high levels of coordination due to the complex nonlinear dynamics of such evasive entities, and the wild environments preclude the use of central coordination units. These aspects lead to the need of distributed estimation and graph-based control protocols. In this work, we propose CIC (Coordinated Implicit Control), a distributed control protocol that is composed by two main blocks. The first is an Implicit Control module that is able to stabilize any continuous input-nonaffine system, tackling the complex nature of the herd dynamics. The second is an Extended Certifiable Optimal Distributed Kalman Filter that, by defining the multi-robot team as a distributed communication graph, allows each robot to rapidly recover the information necessary to compute the control input, while accounting for potential uncertainties. Different experiments validate the proposal.