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A Global/Local Path Planner for Multi-Robot Systems with Uncertain Robot Localization

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Abstract

This paper proposes a path planner for multi-robot systems based on the solution of the multiple traveling salesman problem by genetic algorithm. The main planning goal is to build an efficient path to each robot of the system which jointly ensures that several a priori known points (ways-points) in the environment can be attained by at least one of the robots. During navigation, each robot try to follow its planned path while performing tasks and deviating from unknown static and dynamic obstacles. As the robots have limited sensing and communication skills, their positions can easily become uncertain and the robots will be unable to follow their planned paths. To circumvent this problem, each robot has a local planner, able to recalculate its position and then to resume its planned path. This computation is based on the knowledge about way-points positions, information exchanged with other robots and a self localization algorithm by triangulation. The proposed global/local path planner is firstly validated by computer simulations. An experimental study is also carried out with a small system with very simple mobile robots with differential drive and Bluetooth communication. The obtained results confirm the efficacy of the proposed path planner.

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Acknowledgements

The authors acknowledge financial support from Brazilian Research Council (CNPq) for grants 305816/2014-4 and 309119/2015-4.

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Correspondence to João Paulo Lima Silva de Almeida.

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de Almeida, J.P.L.S., Nakashima, R.T., Neves-Jr, F. et al. A Global/Local Path Planner for Multi-Robot Systems with Uncertain Robot Localization. J Intell Robot Syst 100, 311–333 (2020). https://doi.org/10.1007/s10846-020-01196-y

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