{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,6]],"date-time":"2025-12-06T16:45:08Z","timestamp":1765039508861,"version":"build-2065373602"},"reference-count":45,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2020,3,13]],"date-time":"2020-03-13T00:00:00Z","timestamp":1584057600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the Key Research and Development Project of Science &amp; Technology Department of Sichuan Province","award":["2019YFG0205"],"award-info":[{"award-number":["2019YFG0205"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Searching multiple targets with swarm robots is a realistic and significant problem. The goal is to search the targets in the minimum time while avoiding collisions with other robots. In this paper, inspired by pedestrian behavior, swarm robotic pedestrian behavior (SRPB) was proposed. It considered many realistic constraints in the multi-target search problem, including limited communication range, limited working time, unknown sources, unknown extrema, the arbitrary initial location of robots, non-oriented search, and no central coordination. The performance of different cooperative strategies was evaluated in terms of average time to find the first, the half, and the last source, the number of located sources and the collision rate. Several experiments with different target signals, fixed initial location, arbitrary initial location, different population sizes, and the different number of targets were implemented. It was demonstrated by numerous experiments that SRPB had excellent stability, quick source seeking, a high number of located sources, and a low collision rate in various search strategies.<\/jats:p>","DOI":"10.3390\/s20061606","type":"journal-article","created":{"date-parts":[[2020,3,18]],"date-time":"2020-03-18T08:13:27Z","timestamp":1584519207000},"page":"1606","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["A Distributed Strategy for Cooperative Autonomous Robots Using Pedestrian Behavior for Multi-Target Search in the Unknown Environment"],"prefix":"10.3390","volume":"20","author":[{"given":"Haiyun","family":"Shi","sequence":"first","affiliation":[{"name":"College of Electronics and Information Engineering, Sichuan University, 610065 Chengdu, China"}]},{"given":"Jie","family":"Li","sequence":"additional","affiliation":[{"name":"The Institute of Computer Science, The Beijing University of Posts and Telecommunications, 100876 Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5571-0518","authenticated-orcid":false,"given":"Zhi","family":"Li","sequence":"additional","affiliation":[{"name":"College of Electronics and Information Engineering, Sichuan University, 610065 Chengdu, China"},{"name":"Key Laboratory of Wireless Power Transmission of Ministry of Education, Sichuan University, 610065 Chengdu, China"}]}],"member":"1968","published-online":{"date-parts":[[2020,3,13]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"292","DOI":"10.1016\/j.neucom.2015.05.116","article-title":"A review of swarm robotics tasks","volume":"172","year":"2016","journal-title":"Neurocomputing"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"76","DOI":"10.1016\/j.copbio.2017.01.009","article-title":"Environmental monitoring using autonomous vehicles: A survey of recent searching techniques","volume":"45","author":"Bayat","year":"2017","journal-title":"Curr. 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