NDLI: Probabilistic verification of a decentralized policy for conflict resolution in multi-agent systems

Content Provider	IEEE Xplore Digital Library
Author	Pallottino, L. Scordio, V.G. Frazzoli, E. Bicchi, A.
Copyright Year	2006
Description	Author affiliation: Interdepartmental Res. Center, Pisa Univ. (Pallottino, L.; Scordio, V.G.)
Abstract	In this paper, we consider a decentralized cooperative control policy proposed recently for steering multiple nonholonomic vehicles between assigned start and goal configurations while avoiding collisions. The policy is known to ensure safety (i.e., collision avoidance) for an arbitrarily large number of vehicles, if initial configurations satisfy certain conditions. The method is highly scalable, and effective solutions can be obtained for several tens of autonomous agents. On the other hand, the liveness properties of the policy, i.e. the capability of negotiating a solution in finite time, are not completely understood yet. In this paper, we introduce a condition on the final vehicle configurations, which we conjecture to be necessary and sufficient for guaranteeing liveness. We prove the necessity by a constructive method. Because of the overwhelming complexity of proving the sufficiency of such condition, we assess the correctness of the conjecture in probability through the analysis of the results of a large number of randomized experiments
Sponsorship	IEEE Robotics and Autom. Soc
Starting Page	2448
Ending Page	2453
File Size	711829
Page Count	6
File Format	PDF
ISBN	0780395050
ISSN	10504729
DOI	10.1109/ROBOT.2006.1642069
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-05-15
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Multiagent systems Robot kinematics Air traffic control Remotely operated vehicles Vehicle safety Robotics and automation Distributed control Intelligent transportation systems Aircraft Collision avoidance
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Control and Systems Engineering Electrical and Electronic Engineering Software

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