{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,27]],"date-time":"2026-07-27T18:49:12Z","timestamp":1785178152999,"version":"3.55.0"},"reference-count":69,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2024,1,17]],"date-time":"2024-01-17T00:00:00Z","timestamp":1705449600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000780","name":"European Union Horizon 2020 Framework Programme\u2014project SHERLOCK","doi-asserted-by":"publisher","award":["820689"],"award-info":[{"award-number":["820689"]}],"id":[{"id":"10.13039\/501100000780","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Tracking human operators working in the vicinity of collaborative robots can improve the design of safety architecture, ergonomics, and the execution of assembly tasks in a human\u2013robot collaboration scenario. Three commercial spatial computation kits were used along with their Software Development Kits that provide various real-time functionalities to track human poses. The paper explored the possibility of combining the capabilities of different hardware systems and software frameworks that may lead to better performance and accuracy in detecting the human pose in collaborative robotic applications. This study assessed their performance in two different human poses at six depth levels, comparing the raw data and noise-reducing filtered data. In addition, a laser measurement device was employed as a ground truth indicator, together with the average Root Mean Square Error as an error metric. The obtained results were analysed and compared in terms of positional accuracy and repeatability, indicating the dependence of the sensors\u2019 performance on the tracking distance. A Kalman-based filter was applied to fuse the human skeleton data and then to reconstruct the operator\u2019s poses considering their performance in different distance zones. The results indicated that at a distance less than 3 m, Microsoft Azure Kinect demonstrated better tracking performance, followed by Intel RealSense D455 and Stereolabs ZED2, while at ranges higher than 3 m, ZED2 had superior tracking performance.<\/jats:p>","DOI":"10.3390\/s24020578","type":"journal-article","created":{"date-parts":[[2024,1,17]],"date-time":"2024-01-17T07:41:28Z","timestamp":1705477288000},"page":"578","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["On the Evaluation of Diverse Vision Systems towards Detecting Human Pose in Collaborative Robot Applications"],"prefix":"10.3390","volume":"24","author":[{"given":"Aswin K.","family":"Ramasubramanian","sequence":"first","affiliation":[{"name":"Laboratory for Advanced Manufacturing Simulation and Robotics, School of Mechanical and Materials Engineering, University College Dublin, Belfield, D04 V1W8 Dublin, Ireland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0271-8326","authenticated-orcid":false,"given":"Marios","family":"Kazasidis","sequence":"additional","affiliation":[{"name":"Laboratory for Advanced Manufacturing Simulation and Robotics, School of Mechanical and Materials Engineering, University College Dublin, Belfield, D04 V1W8 Dublin, Ireland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Barry","family":"Fay","sequence":"additional","affiliation":[{"name":"Laboratory for Advanced Manufacturing Simulation and Robotics, School of Mechanical and Materials Engineering, University College Dublin, Belfield, D04 V1W8 Dublin, Ireland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0443-221X","authenticated-orcid":false,"given":"Nikolaos","family":"Papakostas","sequence":"additional","affiliation":[{"name":"Laboratory for Advanced Manufacturing Simulation and Robotics, School of Mechanical and Materials Engineering, University College Dublin, Belfield, D04 V1W8 Dublin, Ireland"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,1,17]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"499","DOI":"10.1016\/j.cirp.2019.04.011","article-title":"Digital Twin Driven Human\u2013Robot Collaborative Assembly","volume":"68","author":"Bilberg","year":"2019","journal-title":"CIRP Annals."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1151","DOI":"10.1016\/j.promfg.2020.01.204","article-title":"Experiences and Expectations of Collaborative Robots in Industry and Academia: Barriers and Development Needs","volume":"38","author":"Aaltonen","year":"2019","journal-title":"Procedia Manuf."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1016\/j.ijpe.2019.01.004","article-title":"Industry 4.0 Technologies: Implementation Patterns in Manufacturing Companies","volume":"210","author":"Frank","year":"2019","journal-title":"Int. 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