{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,28]],"date-time":"2026-09-28T08:55:04Z","timestamp":1790585704198,"version":"4.1.0"},"reference-count":14,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,9,28]],"date-time":"2026-09-28T00:00:00Z","timestamp":1790553600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Robot. AI"],"abstract":"<jats:p>Autonomous exploration is a critical challenge in the use of robots across many applications. Nonetheless, current methodologies exhibit inadequate exploration rates, principally attributable to limited global coverage and infrequent decision-making. To mitigate these restrictions, we offer EMREL (Efficient Multi-Robot Exploration), a hybrid optimization method intended to enable rapid multi-robot exploration in intricate, unfamiliar environments. Our methodology implements the deterministic Coordinated Multi-Robot Exploration (CME) formulation, with cost and utility values organized into a Frontier Information Structure (FIS) shared across all robots. The deterministic cost and utility initially direct the prioritization of neighboring cells surrounding each robot. Subsequently, the stochastic optimizer (Crayfish Optimizer) enhances search space by improving overall solutions. This suggests that robots first evaluate their environment using a deterministic method before moving forward under the control of a stochastic algorithm. We evaluated the suggested hybrid technique on both ordinary and complicated maps and compared it with contemporary algorithms. The simulations show that the proposed method outperforms the contemporary algorithms in exploration rate, temporal efficiency, and number of failed simulation runs. These research results demonstrate the potential of EMREL as a versatile, superior, and efficient approach for robotic exploration, establishing a framework for potential developments in multi-robot system design.<\/jats:p>","DOI":"10.3389\/frobt.2026.1781310","type":"journal-article","created":{"date-parts":[[2026,9,28]],"date-time":"2026-09-28T07:55:56Z","timestamp":1790582156000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Efficient multi-robot exploration using deterministic and metaheuristic methods"],"prefix":"10.3389","volume":"13","author":[{"given":"Faiza","family":"Gul","sequence":"first","affiliation":[{"name":"Department of Electrical Engineering, Air University, Aerospace and Aviation","place":["Kamra Kalan, Pakistan"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Imran","family":"Mir","sequence":"additional","affiliation":[{"name":"Department of Avionics, Air University, Aerospace and Aviation","place":["Kamra Kalan, Pakistan"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Manzar","family":"Abbas","sequence":"additional","affiliation":[{"name":"Department of Avionics, Air University, Aerospace and Aviation","place":["Kamra Kalan, Pakistan"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Agostino","family":"Forestiero","sequence":"additional","affiliation":[{"name":"Institute for High-Performance Computing and Networking, National Research Council of Italy, University of Calabria","place":["Rende, Italy"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,9,28]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"48","DOI":"10.1109\/mis.2017.4531226","article-title":"Multirobot exploration of communication-restricted environments: a survey","volume":"32","author":"Amigoni","year":"2017","journal-title":"IEEE Intell. Syst."},{"key":"B2","doi-asserted-by":"publisher","first-page":"376","DOI":"10.1109\/tro.2004.839232","article-title":"Coordinated multi-robot exploration","volume":"21","author":"Burgard","year":"2005","journal-title":"IEEE Trans. Robotics"},{"key":"B3","doi-asserted-by":"publisher","first-page":"17298806261439742","DOI":"10.1177\/17298806261439742","article-title":"An information-driven pomdp framework for multi-robot formation in autonomous search and rescue","volume":"23","author":"Chang","year":"2026","journal-title":"Int. J. Adv. Robotic Syst."},{"key":"B4","doi-asserted-by":"publisher","first-page":"26196","DOI":"10.1038\/s41598-025-08194-w","article-title":"Multi robot exploration using an advanced multi-objective salp swarm algorithm for efficient coverage and performance","volume":"15","author":"El Romeh","year":"2025","journal-title":"Sci. Rep."},{"key":"B5","doi-asserted-by":"publisher","first-page":"46","DOI":"10.1109\/2.30720","article-title":"Using occupancy grids for mobile robot perception and navigation","volume":"22","author":"Elfes","year":"1989","journal-title":"Computer"},{"key":"B6","first-page":"875","article-title":"A behaviour-based optimisation strategy for multi-robot exploration","author":"Fang","year":"2004"},{"key":"B7","first-page":"1","article-title":"Coordinated multi-robot exploration and slime mould algorithm for multi-robot space exploration","author":"Gudivaka","year":"2024"},{"key":"B8","doi-asserted-by":"publisher","first-page":"1919","DOI":"10.1007\/s10462-023-10567-4","article-title":"Crayfish optimization algorithm","volume":"56","author":"Jia","year":"2023","journal-title":"Artif. Intell. Rev."},{"key":"B9","doi-asserted-by":"publisher","first-page":"2931","DOI":"10.3390\/app9142931","article-title":"Multi-robot exploration based on multi-objective grey wolf optimizer","volume":"9","author":"Kamalova","year":"2019","journal-title":"Appl. Sci."},{"key":"B10","article-title":"A hierarchical region-based approach for efficient multi-robot exploration","author":"Meng","year":"2025","journal-title":"arXiv preprint arXiv:2503.12876"},{"key":"B11","doi-asserted-by":"publisher","first-page":"191617","DOI":"10.1109\/access.2020.3030190","article-title":"Collaborative multi-robot search and rescue: planning, coordination, perception, and active vision","volume":"8","author":"Queralta","year":"2020","journal-title":"IEEE Access"},{"key":"B12","doi-asserted-by":"publisher","first-page":"2156","DOI":"10.3390\/s23042156","article-title":"Multi-robot exploration of unknown space using combined meta-heuristic salp swarm algorithm and deterministic coordinated multi-robot exploration","volume":"23","author":"Romeh","year":"2023","journal-title":"Sensors"},{"key":"B13","doi-asserted-by":"publisher","first-page":"2474","DOI":"10.3390\/math11112474","article-title":"Hybrid vulture-coordinated multi-robot exploration: a novel algorithm for optimization of multi-robot exploration","volume":"11","author":"Romeh","year":"2023","journal-title":"Mathematics"},{"key":"B14","first-page":"146","article-title":"A frontier-based approach for autonomous exploration","author":"Yamauchi","year":"1997"}],"container-title":["Frontiers in Robotics and AI"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/frobt.2026.1781310\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,28]],"date-time":"2026-09-28T07:55:57Z","timestamp":1790582157000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/frobt.2026.1781310\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9,28]]},"references-count":14,"alternative-id":["10.3389\/frobt.2026.1781310"],"URL":"https:\/\/doi.org\/10.3389\/frobt.2026.1781310","relation":{},"ISSN":["2296-9144"],"issn-type":[{"value":"2296-9144","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,9,28]]},"article-number":"1781310"}}