Model predictive path-space iteration for multi-robot coordination

Abstract

In this work, two novel optimization-based strategies for multi-robot coordination are presented. The proposed algorithms employ a model predictive control (MPC) version of a Newton-type approach for solving the underlying optimization problem. Both methods can generate control inputs for vehicles with nonholonomic constraints moving in a configuration space cluttered by obstacles. Obstacle- and inter-collision constraints are incorporated into the optimization problem by using interior and exterior penalty function approaches. Moreover, convergence of the algorithms is studied with and without the presence of obstacles in the environment. Simulation results verify the validity of the proposed methodology. © 2007 Springer-Verlag Berlin Heidelberg.