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dc.contributor.authorZhou, Yuanen_US
dc.contributor.authorHu, Hesuanen_US
dc.contributor.authorLiu, Yangen_US
dc.contributor.authorLin, Shang-Weien_US
dc.contributor.authorDing, Zuohuaen_US
dc.identifier.citationZhou, Y., Hu, H., Liu, Y., Lin, S. & Ding, Z. (2019). A distributed method to avoid higher-order deadlocks in multi-robot systems. Automatica, 112, 108706-.
dc.description.abstractDeadlock avoidance is a crucial problem in motion control of multi-robot systems since deadlocks can crash the systems and ∕or degrade their performance. However, deadlocks sometimes are difficult to predict in advance because of the existence of higher-order deadlocks, from which a system can lead to a deadlock inevitably. In this paper, we investigate the properties of higher-order deadlocks and propose a distributed approach to their avoidance in multi-robot systems where each robot has a predetermined and closed path to execute persistent motion. After modeling the motion of robots by labeled transition systems (LTSs), we first conclude that there exist at most the (N−3)-th order deadlocks with N robots. This means that deadlocks, if any, will occur unavoidably within N−3 steps of corresponding transitions. A distributed algorithm is then proposed to avoid deadlocks in such systems. In the algorithm, each robot only needs to look ahead at most N−1 states, i.e., N−3 intermediate states and two endpoint states, to decide whether its move can cause higher-order deadlocks. To execute the algorithm, each robot needs to communicate with its neighbors. The theoretical analysis and experimental study show that the proposed algorithm is practically operative.en_US
dc.description.sponsorshipMinistry of Education (MOE)en_US
dc.rights© 2019 Elsevier Ltd. All rights reserved.en_US
dc.subjectEngineering::Computer science and engineeringen_US
dc.titleA distributed method to avoid higher-order deadlocks in multi-robot systemsen_US
dc.typeJournal Articleen
dc.contributor.schoolSchool of Computer Science and Engineeringen_US
dc.subject.keywordsAutonomous Mobile Robotsen_US
dc.description.acknowledgementThis work was supported by the Natural Science Foundation of China under Grant Nos. 61573265, 61203037, 51305321, 61751210, 61572441, and 61973242, Fundamental ResearchFunds for the Central Universities under Grant Nos. K7215581201, K5051304004, and K5051304021, New Century Excellent Talents in University under Grant No. NCET-12-0921, and Academic Research Fund Tier 2 by Ministry of Education in Singapore under Grant No. MOE2015-T2-2-049.en_US
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