{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,7]],"date-time":"2026-07-07T15:37:07Z","timestamp":1783438627437,"version":"3.54.6"},"reference-count":37,"publisher":"MDPI AG","issue":"14","license":[{"start":{"date-parts":[[2019,7,13]],"date-time":"2019-07-13T00:00:00Z","timestamp":1562976000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Key R &amp; D project of Shandong Province","award":["2018YFJH0704"],"award-info":[{"award-number":["2018YFJH0704"]}]},{"DOI":"10.13039\/501100001809","name":"Natural Science Foundation of China","doi-asserted-by":"publisher","award":["51609120"],"award-info":[{"award-number":["51609120"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Science and Technology Plan for Shandong University","award":["J16LB7"],"award-info":[{"award-number":["J16LB7"]}]},{"name":"Scientific Research Foundation of Chongqing Education Commission","award":["KJ1600509"],"award-info":[{"award-number":["KJ1600509"]}]},{"name":"Foundation and Frontier Projects of Chongqing Science and Technology Commission","award":["cstc2016jcyjA0561"],"award-info":[{"award-number":["cstc2016jcyjA0561"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Multi-sensor fusion for unmanned surface vehicles (USVs) is an important issue for autonomous navigation of USVs. In this paper, an improved particle swarm optimization (PSO) is proposed for real-time autonomous navigation of a USV in real maritime environment. To overcome the conventional PSO\u2019s inherent shortcomings, such as easy occurrence of premature convergence and human experience-determined parameters, and to enhance the precision and algorithm robustness of the solution, this work proposes three optimization strategies: linearly descending inertia weight, adaptively controlled acceleration coefficients, and random grouping inversion. Their respective or combinational effects on the effectiveness of path planning are investigated by Monte Carlo simulations for five TSPLIB instances and application tests for the navigation of a self-developed unmanned surface vehicle on the basis of multi-sensor data. Comparative results show that the adaptively controlled acceleration coefficients play a substantial role in reducing the path length and the linearly descending inertia weight help improve the algorithm robustness. Meanwhile, the random grouping inversion optimizes the capacity of local search and maintains the population diversity by stochastically dividing the single swarm into several subgroups. Moreover, the PSO combined with all three strategies shows the best performance with the shortest trajectory and the superior robustness, although retaining solution precision and avoiding being trapped in local optima require more time consumption. The experimental results of our USV demonstrate the effectiveness and efficiency of the proposed method for real-time navigation based on multi-sensor fusion.<\/jats:p>","DOI":"10.3390\/s19143096","type":"journal-article","created":{"date-parts":[[2019,7,15]],"date-time":"2019-07-15T04:55:27Z","timestamp":1563166527000},"page":"3096","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":55,"title":["Application of Improved Particle Swarm Optimization for Navigation of Unmanned Surface Vehicles"],"prefix":"10.3390","volume":"19","author":[{"given":"Junfeng","family":"Xin","sequence":"first","affiliation":[{"name":"College of Electromechanical Engineering, Qingdao University of Science and Technology, Qingdao 266061, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shixin","family":"Li","sequence":"additional","affiliation":[{"name":"College of Electromechanical Engineering, Qingdao University of Science and Technology, Qingdao 266061, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jinlu","family":"Sheng","sequence":"additional","affiliation":[{"name":"Transport College, Chongqing Jiaotong University, Chongqing 400074, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yongbo","family":"Zhang","sequence":"additional","affiliation":[{"name":"Qingdao National Marine Science Research Center, Qingdao 266071, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0822-7771","authenticated-orcid":false,"given":"Ying","family":"Cui","sequence":"additional","affiliation":[{"name":"College of Electromechanical Engineering, Qingdao University of Science and Technology, Qingdao 266061, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2019,7,13]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"20","DOI":"10.4031\/MTSJ.44.4.5","article-title":"BathyBoat: An Autonomous Surface Vessel for Stand-alone Survey and Underwater Vehicle Network Supervision","volume":"44","author":"Brown","year":"2010","journal-title":"Mar. 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