Distributed Value Functions for MultiRobot exploration - Archive ouverte HAL Accéder directement au contenu
Communication Dans Un Congrès Année : 2012

Distributed Value Functions for MultiRobot exploration

Résumé

This paper addresses the problem of exploring an unknown area with a team of autonomous robots using decentralized decision making techniques. The localization aspect is not considered and it is assumed the robots share their positions and have access to a map updated with all explored areas. A key problem is then the coordination of decentralized decision processes: each individual robot must choose appropriate exploration goals so that the team simultaneously explores different locations of the environment. We formalize this problem as a Decentralized Markov Decision Process (Dec-MDP) solved as a set of individual MDPs, where interactions between MDPs are considered in a distributed value function. Thus each robot computes locally a strategy that minimizes the interactions between the robots and maximizes the space coverage of the team. Our technique has been implemented and evaluated in real-world and simulated experiments.
Fichier principal
Vignette du fichier
DistributedValueFunctionsForMultiRobotExploration_ICRA2012.pdf (1.89 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-00969562 , version 1 (23-01-2017)

Identifiants

  • HAL Id : hal-00969562 , version 1

Citer

Laëtitia Matignon, Laurent Jeanpierre, Abdel-Illah Mouaddib. Distributed Value Functions for MultiRobot exploration. IEEE International Conference on Robotics and Automation (ICRA), 2012, St paul - Minnesota, United States. ⟨hal-00969562⟩
117 Consultations
190 Téléchargements

Partager

Gmail Facebook X LinkedIn More