Chapter

Cooperative Systems

Volume 588 of the series Lecture Notes in Economics and Mathematical Systems pp 229-253

Model Predictive Path-Space Iteration for Multi-Robot Coordination

  • Omar A. A. OrquedaAffiliated withMARHES Laboratory, School of Electrical and Computer Engineering, Oklahoma State University
  • , Rafael FierroAffiliated withMARHES Laboratory, School of Electrical and Computer Engineering, Oklahoma State University

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Summary

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.