{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T01:23:39Z","timestamp":1760059419589,"version":"build-2065373602"},"reference-count":41,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2025,6,14]],"date-time":"2025-06-14T00:00:00Z","timestamp":1749859200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["52472347","52331012","52071200","KLGLIT2024ZD001"],"award-info":[{"award-number":["52472347","52331012","52071200","KLGLIT2024ZD001"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Open Fund of Chongqing Key Laboratory of Green Logistics Intelligent Technology (Chongqing Jiaotong University)","award":["52472347","52331012","52071200","KLGLIT2024ZD001"],"award-info":[{"award-number":["52472347","52331012","52071200","KLGLIT2024ZD001"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JMSE"],"abstract":"<jats:p>Unmanned boat distance detection is an important foundation for autonomous navigation tasks of unmanned boats. Monocular vision ranging has the advantages of low hardware equipment requirements, simple deployment, and high efficiency of distance detection. Unmanned boats can sense the real-time navigational situation of waters through monocular vision ranging, providing data support for their autonomous navigation. This paper establishes a framework for unmanned boat distance detection. The framework extracts and recognizes the features of an unmanned boat through Yolov11m-pose and selects the key points of the ship for physical distance mapping. Using the camera calibration to obtain the pixel focal length, the main point coordinates and other parameters are obtained. The number of pixel points in the image key point to the image center pixel and the actual distance of the camera from the horizontal plane are combined with the focal length of the camera for triangular similarity conversion. These data are fused with the camera pitch angle and other parameters to obtain the final distance. At the same time, experimental verification of the key point detection model demonstrates that it fully meets the requirements for unmanned boat ranging tasks, as assessed by Precision, Recall, mAP50, mAP50-95 and other indicators. These indicators show that Yolov11m-pose has a better accuracy in the key point detection task with an unmanned boat. The verification experiments also illustrate the accuracy of the key point-based physical distance mapping compared with the traditional detection frame-based physical distance mapping, which was assessed by the mean squared error (MSE), the root mean square error (RMSE), and the mean absolute error (MAE). The metrics show that key point-based unmanned boat distance mapping has greater accuracy in a variety of environmental situations, which verifies the effectiveness of this approach.<\/jats:p>","DOI":"10.3390\/jmse13061172","type":"journal-article","created":{"date-parts":[[2025,6,16]],"date-time":"2025-06-16T04:06:24Z","timestamp":1750046784000},"page":"1172","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Monocular Unmanned Boat Ranging System Based on YOLOv11-Pose Critical Point Detection and Camera Geometry"],"prefix":"10.3390","volume":"13","author":[{"given":"Yuzhen","family":"Wu","sequence":"first","affiliation":[{"name":"Institute of Logistics Science and Engineering, Shanghai Maritime University, Shanghai 201306, China"},{"name":"SPG Qingdao Port Group Co., Ltd., Qingdao 266011, China"}]},{"given":"Yucheng","family":"Suo","sequence":"additional","affiliation":[{"name":"Merchant Marine College, Shanghai Maritime University, Shanghai 201306, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8959-5108","authenticated-orcid":false,"given":"Xinqiang","family":"Chen","sequence":"additional","affiliation":[{"name":"Institute of Logistics Science and Engineering, Shanghai Maritime University, Shanghai 201306, China"},{"name":"Chongqing Key Laboratory of Green Logistics Intelligent Technology, Chongqing Jiaotong University, Chongqing 400074, China"}]},{"given":"Yongsheng","family":"Yang","sequence":"additional","affiliation":[{"name":"Institute of Logistics Science and Engineering, Shanghai Maritime University, Shanghai 201306, China"}]},{"given":"Han","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Marine Science and Engineering, Shanghai Maritime University, Shanghai 201306, China"}]},{"given":"Zichuang","family":"Wang","sequence":"additional","affiliation":[{"name":"Shanghai Ship and Shipping Research Institute Co., Ltd., Shanghai 201306, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5055-6347","authenticated-orcid":false,"given":"Octavian","family":"Postolache","sequence":"additional","affiliation":[{"name":"Instituto de Telecomunica\u00e7\u00f5es (IT), North Tower, 10th Floor, Av. Rovisco Pais 1, 1049-001 Lisbon, Portugal"},{"name":"Department of Information Science and Technology, Iscte\u2014Instituto Universit\u00e1rio de Lisboa, Av. das For\u00e7as Armadas, 1649-026 Lisbon, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2025,6,14]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"127534","DOI":"10.1016\/j.eswa.2025.127534","article-title":"Unmanned surface vessel routing and unmanned aerial vehicle swarm scheduling for off-shore wind turbine blade inspection","volume":"284","author":"Ismail","year":"2025","journal-title":"Expert Syst. Appl."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"120606","DOI":"10.1016\/j.oceaneng.2025.120606","article-title":"State estimation of marine vessels affected by waves by unmanned aerial vehicles","volume":"323","author":"Saska","year":"2025","journal-title":"Ocean. 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