{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,5]],"date-time":"2026-01-05T04:03:42Z","timestamp":1767585822155,"version":"build-2065373602"},"reference-count":73,"publisher":"MDPI AG","issue":"19","license":[{"start":{"date-parts":[[2019,9,21]],"date-time":"2019-09-21T00:00:00Z","timestamp":1569024000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"State Key Laboratory of Robotics Foundation","award":["nos. 2016-Z08","nos. 2017-Z05"],"award-info":[{"award-number":["nos. 2016-Z08","nos. 2017-Z05"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The advent of the swarm makes it feasible to dynamically monitor a wide area for maritime applications. The crucial problems of underwater swarm monitoring are communication and behavior coordination. To tackle these problems, we propose a wide area monitoring strategy that searches for static targets of interest simultaneously. Traditionally, an underwater robot adopts either acoustic communication or optical communication. However, the former is low in bandwidth and the latter is short in communication range. Our strategy coordinates underwater robots through indirect communication, which is inspired by social insects that exchange information by pheromone. The indirect communication is established with the help of a set of underwater communication nodes. We adopt a virtual pheromone-based controller and provide a set of rules to integrate the area of interest into the pheromone. Based on the information in the virtual pheromone, behavior laws are developed to guide the swarm to monitor and search with nearby information. In addition, a robot can improve its performance when using additional far-away pheromone information. The monitoring strategy is further improved by adopting a swarm evolution scheme which automatically adjusts the visiting period. Experimental results show that our strategy is superior to the random strategy in most cases.<\/jats:p>","DOI":"10.3390\/s19194089","type":"journal-article","created":{"date-parts":[[2019,9,23]],"date-time":"2019-09-23T03:26:32Z","timestamp":1569209192000},"page":"4089","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":19,"title":["A Pheromone-Inspired Monitoring Strategy Using a Swarm of Underwater Robots"],"prefix":"10.3390","volume":"19","author":[{"given":"Guannan","family":"Li","sequence":"first","affiliation":[{"name":"State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China"},{"name":"Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110016, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6488-224X","authenticated-orcid":false,"given":"Chao","family":"Chen","sequence":"additional","affiliation":[{"name":"Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences (CAS), Shenzhen 518055, China"}]},{"given":"Chao","family":"Geng","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China"},{"name":"Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110016, China"},{"name":"School of Information Science and Engineering, Northeastern University, Shenyang 110819, China"}]},{"given":"Meng","family":"Li","sequence":"additional","affiliation":[{"name":"The School of Information and Science Technology, Zhejiang Sci-Tech University (ZSTU), Hangzhou 310018, China"}]},{"given":"Hongli","family":"Xu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China"},{"name":"Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110016, China"}]},{"given":"Yang","family":"Lin","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China"},{"name":"Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110016, China"}]}],"member":"1968","published-online":{"date-parts":[[2019,9,21]]},"reference":[{"key":"ref_1","first-page":"1","article-title":"On the designing principles and optimization approaches of bio-inspired self-organized network: A survey","volume":"56","author":"Zhang","year":"2013","journal-title":"Sci. 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