{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,15]],"date-time":"2026-09-15T08:13:26Z","timestamp":1789460006384,"version":"build-2803163510"},"reference-count":48,"publisher":"IOP Publishing","issue":"5","license":[{"start":{"date-parts":[[2026,9,15]],"date-time":"2026-09-15T00:00:00Z","timestamp":1789430400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/publishingsupport.iopscience.iop.org\/iop-standard\/v1"},{"start":{"date-parts":[[2026,9,15]],"date-time":"2026-09-15T00:00:00Z","timestamp":1789430400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/iopscience.iop.org\/info\/page\/text-and-data-mining"}],"funder":[{"name":"Nansha District Science and Technology Program","award":["2024ZD019"],"award-info":[{"award-number":["2024ZD019"]}]}],"content-domain":{"domain":["iopscience.iop.org"],"crossmark-restriction":false},"short-container-title":["Bioinspir. Biomim."],"published-print":{"date-parts":[[2026,10,30]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>\n                    Dual-arm robots are gaining prominence in modern industrial automation, particularly in smart manufacturing, driven by their exceptional flexibility, collaborative potential, and anthropomorphic design. Modern applications increasingly demand capabilities in complex assembly, precision manipulation, and close human-robot interaction. Consequently, integrating dexterous wrist joints into dual-arm systems has emerged as a critical research frontier to enhance their adaptability and collaborative performance. This study presents a lightweight, modular, and dexterous robotic wrist inspired by human wrist anatomy. The physical prototype is highly compact, weighing 496 g with a volume of 436 cm\n                    <jats:sup>3<\/jats:sup>\n                    . Experimental results show that the prototype withstands a payload of up to 2 kg under the evaluated conditions and achieves repeatable coupled tilting motion with a maximum tilt angle of approximately 32\u00b0. The robotic wrist is driven by an encoder-equipped servo motor and incorporates a high-precision inertial measurement unit (IMU) for spatial orientation tracking. Real-time IMU feedback of three-axis angular variations enables dynamic adjustment of the motor torque, thereby ensuring stable payload performance and spatial adaptability. To validate its practical utility, two prototype wrists are integrated into a dual-arm robot, demonstrating enhanced flexibility and bimanual grasping capabilities. Extensive experimental results confirm the effectiveness and real-world applicability of the proposed design.\n                  <\/jats:p>","DOI":"10.1088\/1748-3190\/aea25b","type":"journal-article","created":{"date-parts":[[2026,9,3]],"date-time":"2026-09-03T22:51:31Z","timestamp":1788475891000},"page":"056010","update-policy":"https:\/\/doi.org\/10.1088\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["A versatile dexterous robotic wrist: lightweight, modular, and pose-adaptive"],"prefix":"10.1088","volume":"21","author":[{"given":"Yang","family":"Zhou","sequence":"first","affiliation":[{"name":"South China University of Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chenxi","family":"Qu","sequence":"additional","affiliation":[{"name":"China Academy of Launch Vehicle Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiaqi","family":"Wei","sequence":"additional","affiliation":[{"name":"South China University of Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fenglei","family":"Li","sequence":"additional","affiliation":[{"name":"South China University of Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-1285-9253","authenticated-orcid":true,"given":"Shengguan","family":"Qu","sequence":"additional","affiliation":[{"name":"South China University of Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"266","published-online":{"date-parts":[[2026,9,15]]},"reference":[{"key":"bbaea25bbib1","doi-asserted-by":"publisher","first-page":"466","DOI":"10.1109\/TASE.2024.3352584","type":"journal-article","article-title":"A task-adaptive deep reinforcement learning framework for dual-arm robot manipulation","volume":"22","author":"Cui","year":"2025","journal-title":"IEEE Trans. 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All rights, including for text and data mining, AI training, and similar technologies, are reserved.","name":"copyright_information","label":"Copyright Information"},{"value":"2026-05-12","name":"date_received","label":"Date Received","group":{"name":"publication_dates","label":"Publication dates"}},{"value":"2026-09-03","name":"date_accepted","label":"Date Accepted","group":{"name":"publication_dates","label":"Publication dates"}},{"value":"2026-09-15","name":"date_epub","label":"Online publication date","group":{"name":"publication_dates","label":"Publication dates"}}]}}