{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,7]],"date-time":"2025-11-07T08:33:16Z","timestamp":1762504396637,"version":"build-2065373602"},"reference-count":40,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2020,11,28]],"date-time":"2020-11-28T00:00:00Z","timestamp":1606521600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100010661","name":"Horizon 2020","doi-asserted-by":"publisher","award":["375850"],"award-info":[{"award-number":["375850"]}],"id":[{"id":"10.13039\/100010661","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Robotics"],"abstract":"<jats:p>Modern mobile robots tend to be used in numerous exploration and search and rescue applications. Essentially they are coordinated by human operators and collaborate with inspection or rescue teams. Over the time, robots became more advanced and capable for various autonomous collaborative scenarios. Recent advances in the field of collaborative exploration and coverage provide different approaches to solve this objective. Thus scope of this article is to present a novel collaborative approach for multi-agent coordination in exploration and coverage of unknown complex indoor environments. Fundamentally, the task of collaborative exploration can be divided into two core components. The principal one is a sensor based exploration scheme that aims to guarantee complete area exploration and coverage. The second core component proposed is a staying alive policy that takes under consideration the battery charge level limitation of the agents. From this perspective the path planner assigns feasible tasks to each of the agents, including the capability of providing reachable, collision free paths. The overall efficacy of the proposed approach was extensively evaluated by multiple simulation results in a complex unknown environments.<\/jats:p>","DOI":"10.3390\/robotics9040101","type":"journal-article","created":{"date-parts":[[2020,11,29]],"date-time":"2020-11-29T21:00:57Z","timestamp":1606683657000},"page":"101","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Multi-Agent Collaborative Path Planning Based on Staying Alive Policy"],"prefix":"10.3390","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8235-2728","authenticated-orcid":false,"given":"Anton","family":"Koval","sequence":"first","affiliation":[{"name":"Robotics Team, Department of Computer, Electrical and Space Engineering, Lule\u00e5 University of Technology, SE-97187 Lule\u00e5, Sweden"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7631-002X","authenticated-orcid":false,"given":"Sina","family":"Sharif Mansouri","sequence":"additional","affiliation":[{"name":"Robotics Team, Department of Computer, Electrical and Space Engineering, Lule\u00e5 University of Technology, SE-97187 Lule\u00e5, Sweden"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"George","family":"Nikolakopoulos","sequence":"additional","affiliation":[{"name":"Robotics Team, Department of Computer, Electrical and Space Engineering, Lule\u00e5 University of Technology, SE-97187 Lule\u00e5, Sweden"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,11,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Wasik, A., Pereira, J.N., Ventura, R., Lima, P.U., and Martinoli, A. 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