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Content Provider | IEEE Xplore Digital Library |
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Author | Matignon, L. Jeanpierre, L. Mouaddib, A.-I. |
Copyright Year | 2012 |
Description | Author affiliation: Université de Caen Basse-Normandie, CNRS - UMR6072 GREYC - F-14032 France (Matignon, L.; Jeanpierre, L.; Mouaddib, A.-I.) |
Abstract | 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. |
Starting Page | 1544 |
Ending Page | 1550 |
File Size | 2008242 |
Page Count | 7 |
File Format | |
ISBN | 9781467314039 |
ISSN | 10504729 |
e-ISBN | 9781467314053 |
e-ISBN | 9781467314046 |
DOI | 10.1109/ICRA.2012.6224937 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2012-05-14 |
Publisher Place | USA |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Robot kinematics Robot sensing systems Computational modeling Joints Trajectory Computer architecture |
Content Type | Text |
Resource Type | Article |
Subject | Artificial Intelligence Control and Systems Engineering Electrical and Electronic Engineering Software |
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