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Multi-Robot nonlinear model predictive formation control: the obstacle avoidance problem

Published online by Cambridge University Press:  01 July 2014

Tiago P. Nascimento*
Department of Computer Systems, Informatics Center, Federal University of Paraiba (UFPB), Cidade Universitaria - João Pessoa - PB - Brazil
André G. S. Conceição
LaR - Robotics Lab, Department of Electrical Engineering, Polytechnic School, Federal University of Bahia (UFBA), Rua Aristides Novis, 02 Federação - Salvador-BA - Brazil
António Paulo Moreira
INESC TEC (formerly INESC Porto) and Faculty of Engineering, University of Porto, rua Dr. Roberto Frias, 4200-465 Porto, Portugal
*Corresponding author. E-mail:


This paper discusses about a proposed solution to the obstacle avoidance problem in multi-robot systems when applied to active target tracking. It is explained how a nonlinear model predictive formation control (NMPFC) previously proposed solves this problem of fixed and moving obstacle avoidance. First, an approach is presented which uses potential functions as terms of the NMPFC. These terms penalize the proximity with mates and obstacles. A strategy to avoid singularity problems with the potential functions using a modified A* path planning algorithm was then introduced. Results with simulations and experiments with real robots are presented and discussed demonstrating the efficiency of the proposed approach.

Copyright © Cambridge University Press 2014 

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