Model Predictive Path-Space Iteration for Multi-Robot Coordination

Omar A. A. Orqueda () and Rafael Fierro ()
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Omar A. A. Orqueda: Oklahoma State University
Rafael Fierro: Oklahoma State University

A chapter in Cooperative Systems, 2007, pp 229-253 from Springer

Abstract: 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.

Keywords: Mobile Robot; Path Planning; Model Predictive Control; Obstacle Avoidance; Nonholonomic System (search for similar items in EconPapers)
Date: 2007
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Persistent link: https://EconPapers.repec.org/RePEc:spr:lnechp:978-3-540-48271-0_14

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DOI: 10.1007/978-3-540-48271-0_14

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