{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,19]],"date-time":"2026-08-19T19:58:31Z","timestamp":1787169511023,"version":"build-2736575974"},"reference-count":32,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2019,6,25]],"date-time":"2019-06-25T00:00:00Z","timestamp":1561420800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000808","name":"Fusion for Energy","doi-asserted-by":"publisher","award":["F4E-GRT-0901"],"award-info":[{"award-number":["F4E-GRT-0901"]}],"id":[{"id":"10.13039\/501100000808","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>In this paper, we propose two novel methods for robot-world-hand\u2013eye calibration and provide a comparative analysis against six state-of-the-art methods. We examine the calibration problem from two alternative geometrical interpretations, called \u2018hand\u2013eye\u2019 and \u2018robot-world-hand\u2013eye\u2019, respectively. The study analyses the effects of specifying the objective function as pose error or reprojection error minimization problem. We provide three real and three simulated datasets with rendered images as part of the study. In addition, we propose a robotic arm error modeling approach to be used along with the simulated datasets for generating a realistic response. The tests on simulated data are performed in both ideal cases and with pseudo-realistic robotic arm pose and visual noise. Our methods show significant improvement and robustness on many metrics in various scenarios compared to state-of-the-art methods.<\/jats:p>","DOI":"10.3390\/s19122837","type":"journal-article","created":{"date-parts":[[2019,6,25]],"date-time":"2019-06-25T10:52:31Z","timestamp":1561459951000},"page":"2837","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":72,"title":["Methods for Simultaneous Robot-World-Hand\u2013Eye Calibration: A Comparative Study"],"prefix":"10.3390","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9069-0505","authenticated-orcid":false,"given":"Ihtisham","family":"Ali","sequence":"first","affiliation":[{"name":"Faculty of Information Technology and Communication, Tampere University, 33720 Tampere, Finland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Olli","family":"Suominen","sequence":"additional","affiliation":[{"name":"Faculty of Information Technology and Communication, Tampere University, 33720 Tampere, Finland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Atanas","family":"Gotchev","sequence":"additional","affiliation":[{"name":"Faculty of Information Technology and Communication, Tampere University, 33720 Tampere, Finland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Emilio Ruiz","family":"Morales","sequence":"additional","affiliation":[{"name":"Fusion for Energy (F4E), ITER Delivery Department, Remote Handling Project Team, 08019 Barcelona, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2019,6,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"421","DOI":"10.1177\/0278364917710318","article-title":"Learning hand\u2013eye coordination for robotic grasping with deep learning and large-scale data collection","volume":"37","author":"Levine","year":"2018","journal-title":"Int. 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