{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,4]],"date-time":"2026-08-04T17:14:12Z","timestamp":1785863652534,"version":"3.56.0"},"reference-count":33,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2024,4,16]],"date-time":"2024-04-16T00:00:00Z","timestamp":1713225600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Natural Science Foundation of China","award":["52175478"],"award-info":[{"award-number":["52175478"]}]},{"name":"National Natural Science Foundation of China","award":["52205533"],"award-info":[{"award-number":["52205533"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>In the field of robotic automation, achieving high position accuracy in robotic vision systems (RVSs) is a pivotal challenge that directly impacts the efficiency and effectiveness of industrial applications. This study introduces a comprehensive modeling approach that integrates kinematic and joint compliance factors to significantly enhance the position accuracy of a system. In the first place, we develop a unified kinematic model that effectively reduces the complexity and error accumulation associated with the calibration of robotic systems. At the heart of our approach is the formulation of a joint compliance model that meticulously accounts for the intricacies of the joint connector, the external load, and the self-weight of robotic links. By employing a novel 3D rotary laser sensor for precise error measurement and model calibration, our method offers a streamlined and efficient solution for the accurate integration of vision systems into robotic operations. The efficacy of our proposed models is validated through experiments conducted on a FANUC LR Mate 200iD robot, showcasing notable improvements in the position accuracy of robotic vision system. Our findings contribute a framework for the calibration and error compensation of RVS, holding significant potential for advancements in automated tasks requiring high precision.<\/jats:p>","DOI":"10.3390\/s24082559","type":"journal-article","created":{"date-parts":[[2024,4,17]],"date-time":"2024-04-17T08:22:44Z","timestamp":1713342164000},"page":"2559","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Kinematic and Joint Compliance Modeling Method to Improve Position Accuracy of a Robotic Vision System"],"prefix":"10.3390","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5344-8317","authenticated-orcid":false,"given":"Fan","family":"Ye","sequence":"first","affiliation":[{"name":"School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guangpeng","family":"Jia","sequence":"additional","affiliation":[{"name":"China National Heavy Duty Truck Group Co., Ltd., No. 777 Hua\u2019ao Road, Innovation Zone, Jinan 250101, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1036-7936","authenticated-orcid":false,"given":"Yukun","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0164-6471","authenticated-orcid":false,"given":"Xiaobo","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Juntong","family":"Xi","sequence":"additional","affiliation":[{"name":"School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,4,16]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"108132","DOI":"10.1016\/j.optlaseng.2024.108132","article-title":"Multi-view 3D data fusion and patching to reduce Shannon entropy in Robotic Vision","volume":"177","author":"Sergiyenko","year":"2024","journal-title":"Opt. 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