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While robots possess local perception and limited communication capabilities, they struggle to handle coverage issues in dynamic environments. This paper proposes a self-organizing algorithm for swarm robots based on Dynamic Virtual Force (DVF) to cover dynamic areas. Robots in the swarm can locally perceive their surrounding robots and dynamically select adjacent ones to generate virtual repulsion, thereby controlling their movement. The algorithm enables swarm robots to be rapidly and evenly deployed in unknown areas, adapt to dynamic area changes, and solve the problem of symmetrical robot distribution during coverage. It also allows for adaptive coverage of different density areas, divided as needed. Experimental validation across 20 benchmark scenarios (including obstacles, dynamic boundaries, and multi-density zones) demonstrates that the DVF method outperforms existing approaches in coverage rate, total robot movement distance, and coverage uniformity. The results validate its effectiveness and superiority in addressing area coverage problems. By addressing these challenges, the DVF algorithm can be widely applied to forest firefighting, oil spill cleanup in the ocean, and other swarm robot tasks.<\/jats:p>","DOI":"10.3390\/sym17081202","type":"journal-article","created":{"date-parts":[[2025,7,28]],"date-time":"2025-07-28T14:05:47Z","timestamp":1753711547000},"page":"1202","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Self-Organizing Coverage Method of Swarm Robots Based on Dynamic Virtual Force"],"prefix":"10.3390","volume":"17","author":[{"given":"Maohua","family":"Kuang","sequence":"first","affiliation":[{"name":"Business School, Xiangtan University, Xiangtan 411105, China"},{"name":"Key Laboratory of Intelligent Computing and Information Processing, Ministry of Education, School of Computer Science, Xiangtan 411105, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wei","family":"Yan","sequence":"additional","affiliation":[{"name":"Key Laboratory of Intelligent Computing and Information Processing, Ministry of Education, School of Computer Science, Xiangtan 411105, China"},{"name":"Faculty of School of Computer Science, Xiangtan University, Xiangtan 411105, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qiuzhen","family":"Wang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Intelligent Computing and Information Processing, Ministry of Education, School of Computer Science, Xiangtan 411105, China"},{"name":"Faculty of School of Computer Science, Xiangtan University, Xiangtan 411105, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yue","family":"Zheng","sequence":"additional","affiliation":[{"name":"Key Laboratory of Intelligent Computing and Information Processing, Ministry of Education, School of Computer Science, Xiangtan 411105, China"},{"name":"Faculty of School of Computer Science, Xiangtan University, Xiangtan 411105, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,7,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"180","DOI":"10.1177\/09544062241275359","article-title":"Exploring advancements and emerging trends in robotic swarm coordination and control of swarm flying robots: A review","volume":"239","author":"Alqudsi","year":"2025","journal-title":"Proc. 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