Distributed Encirclement for Multi-Robot Systems using Follow the Optimal Gap Method in Dense Environments

Distributed Encirclement for Multi-Robot Systems using Follow the Optimal Gap Method in Dense Environments | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 13 February 2025 V1 Latest version Share on Distributed Encirclement for Multi-Robot Systems using Follow the Optimal Gap Method in Dense Environments Authors : Jun Luo , Mengdie Huang , Dengyu Xiao [email protected] , and Huayan Pu Authors Info & Affiliations https://doi.org/10.22541/au.173946301.10220905/v1 Published Unmanned Systems Version of record Peer review timeline 257 views 131 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract ： In dense environments, it is challenging for multiple pursuers to capture an evader with an uncertain strategy. When the pursuers start from arbitrary initial positions rather than being evenly distributed around the evader, it becomes even more difficult for them to quickly approach and successfully coordinate to encircle the evader. To address this issue, we present a novel hierarchical framework to address the problem of multi-pursuer evader-approaching and encirclement in dense environments without any initial position constraint. At the high level, a novel task assignment method based on Dynamic Reallocate Review Consensus (DRRC) is proposed to reduce the intersection paths and further resolve allocation conflicts. At the low level, an effective distributed motion planning algorithm based on Follow the Optimal Gap Method (FOGM) is proposed, integrating adaptive safety factor and optimal reciprocal collision avoidance for multi-pursuer’ collision ‐free trajectories, guaranteeing that multi-pursuer can efficiently and safely encircle and capture the evader. Extensive simulation experiments in different hunting scenarios and two real-world experiments validate the applicability and practicability of our methods. Supplementary Material File (distributed encirclement for multi-robot systems using follow the optimal gap method in dense environments.doc) Download 20.07 MB Information & Authors Information Version history V1 Version 1 13 February 2025 Peer review timeline Published Unmanned Systems Version of Record 3 Jan 2026 Published Copyright This work is licensed under a Non Exclusive No Reuse License. Keywords algorithm multi-robot cooperation threat evasion wheeled robotics Authors Affiliations Jun Luo Chongqing University State Key Laboratory of Mechanical Transmission for Advanced Equipment View all articles by this author Mengdie Huang Shanghai University School of Mechatronic Engineering and Automation View all articles by this author Dengyu Xiao [email protected] Chongqing University State Key Laboratory of Mechanical Transmission for Advanced Equipment View all articles by this author Huayan Pu Chongqing University State Key Laboratory of Mechanical Transmission for Advanced Equipment View all articles by this author Metrics & Citations Metrics Article Usage 257 views 131 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Jun Luo, Mengdie Huang, Dengyu Xiao, et al. Distributed Encirclement for Multi-Robot Systems using Follow the Optimal Gap Method in Dense Environments. Authorea . 13 February 2025. 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