DECENTRALIZED MULTI-ROBOT PLANNING TO EXPLORE AND PERCEIVE

Authors

  • Laetitia Matignon Université Lyon 1, LIRIS UMR5205, F-69622, France
  • Laurent Jeanpierre Université Caen Basse-Normandie, GREYC UMR6072, F-14032, France
  • Abdel-Illah Mouaddib Université Caen Basse-Normandie, GREYC UMR6072, F-14032, France

DOI:

https://doi.org/10.14311/AP.2015.55.0169

Keywords:

cooperative multi-robot systems, robot coordination, robot planning, multi-robot exploration, active perception

Abstract

In a recent French robotic contest, the objective was to develop a multi-robot system able to autonomously map and explore an unknown area while also detecting and localizing objects. As a participant in this challenge, we proposed a new decentralized Markov decision process (Dec-MDP) resolution based on distributed value functions (DVF) to compute multi-robot exploration strategies. The idea is to take advantage of sparse interactions by allowing each robot to calculate locally a strategy that maximizes the explored space while minimizing robots interactions. In this paper, we propose an adaptation of this method to improve also object recognition by integrating into the DVF the interest in covering explored areas with photos. The robots will then act to maximize the explored space and the photo coverage, ensuring better perception and object recognition.

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Published

2015-06-30

How to Cite

Matignon, L., Jeanpierre, L., & Mouaddib, A.-I. (2015). DECENTRALIZED MULTI-ROBOT PLANNING TO EXPLORE AND PERCEIVE. Acta Polytechnica, 55(3), 169–176. https://doi.org/10.14311/AP.2015.55.0169

Issue

Section

Articles