{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T02:59:24Z","timestamp":1760151564927,"version":"build-2065373602"},"reference-count":30,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2022,3,30]],"date-time":"2022-03-30T00:00:00Z","timestamp":1648598400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Peipei Zhou","award":["51905557"],"award-info":[{"award-number":["51905557"]}]},{"name":"Shanghai Sailing Program","award":["19YF1418900"],"award-info":[{"award-number":["19YF1418900"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>While Unmanned Aerial Vehicles (UAVs) can be a valuable solution for the damage inspection of port machinery infrastructures, their trajectories are still prone to collision risks, trajectory non-smoothness, and large deviations. This research introduces a trajectory optimization method for inspecting vulnerable parts of a gantry crane by a UAV fitted with a high-definition (HD) camera. We first analyze the vulnerable parts of a gantry crane, then use the A* algorithm to plan a path for the UAV. The trajectory optimization process is divided into two steps, the first is a trajectory correction method and the second is an objective function that applies a minimum snap method while taking into consideration flight corridor constraints. The experimental simulation results show that, compared with previous methods, our approach can not only generate a collision-free and smooth trajectory but also shorten the trajectory length significantly while substantially reducing the maximum deviation average deviation distances. The simulation results show that this modelling approach provides a valuable solution for UAV trajectory planning for gantry crane inspection.<\/jats:p>","DOI":"10.3390\/rs14071658","type":"journal-article","created":{"date-parts":[[2022,3,30]],"date-time":"2022-03-30T21:28:39Z","timestamp":1648675719000},"page":"1658","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["HD Camera-Equipped UAV Trajectory Planning for Gantry Crane Inspection"],"prefix":"10.3390","volume":"14","author":[{"given":"Gang","family":"Tang","sequence":"first","affiliation":[{"name":"Logistics Engineering College, Shanghai Maritime University, Shanghai 201306, China"}]},{"given":"Jiaxu","family":"Gu","sequence":"additional","affiliation":[{"name":"Logistics Engineering College, Shanghai Maritime University, Shanghai 201306, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2707-2533","authenticated-orcid":false,"given":"Weidong","family":"Zhu","sequence":"additional","affiliation":[{"name":"Department of Mechanical Engineering, University of Maryland, Baltimore County, 1000 Hilltop Circle, Baltimore, MD 21250, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5586-1997","authenticated-orcid":false,"given":"Christophe","family":"Claramunt","sequence":"additional","affiliation":[{"name":"Naval Academy, Brest Naval, Lanveoc-Poulmic, BP 600, 29240 Brest, France"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6293-543X","authenticated-orcid":false,"given":"Peipei","family":"Zhou","sequence":"additional","affiliation":[{"name":"School of Mechatronic Engineering, Guangdong Polytechnic Normal University, Guangzhou 510665, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,3,30]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1059","DOI":"10.1007\/s10514-015-9517-1","article-title":"Three-dimensional coverage path planning via viewpoint resampling and tour optimization for aerial robots","volume":"40","author":"Bircher","year":"2016","journal-title":"Auton. 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