{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,20]],"date-time":"2026-01-20T19:14:31Z","timestamp":1768936471276,"version":"3.49.0"},"reference-count":139,"publisher":"Association for Computing Machinery (ACM)","issue":"2","funder":[{"name":"National Science Foundation","award":["2441587"],"award-info":[{"award-number":["2441587"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["J. Hum.-Robot Interact."],"published-print":{"date-parts":[[2026,3,31]]},"abstract":"<jats:p>\n                    Robot teleoperation has become increasingly crucial for extending human capabilities in inaccessible or hazardous environments and facilitating human\u2013robot collaboration. While significant advancements have been made in teleoperation interfaces, the success of these systems critically depends on how effectively humans can interact with and control robotic systems across diverse manipulation tasks. However, existing research primarily evaluates interfaces within specific tasks or applications, lacking systematic assessment across different manipulation scenarios. This limitation leads to suboptimal interface selection that can compromise task efficiency in critical domains and impede the collection of high-quality demonstrations for robot learning. To address these gaps, we first introduce a novel two-axis Robotic Manipulation Task Taxonomy that systematically categorizes manipulation tasks based on their fundamental control requirements: Motion Type (translation-dominant vs. rotation-dominant) and Engagement Type (rigid vs. non-rigid object interactions). We conducted a comprehensive user study (\n                    <jats:inline-formula content-type=\"math\/tex\">\n                      <jats:tex-math notation=\"LaTeX\" version=\"MathJax\">\\(n=30\\)<\/jats:tex-math>\n                    <\/jats:inline-formula>\n                    ) evaluating three distinct teleoperation interfaces (Gamepad, 3D Mouse, and Virtual Reality (VR) Controller) based on this taxonomy. Our results indicate that the Gamepad and 3D mouse significantly outperformed the VR Controller in task completion time across all task categories. In contrast, the VR Controller showed higher first-attempt success rates but caused significantly greater cognitive load across all NASA Task Load Index (NASA-TLX) subscales compared to the Gamepad interface, and specifically higher mental demand, physical demand, and effort compared to the 3D mouse. Our results also indicate that although prior familiarity with an interface lowered perceived workload and enhanced perceived performance, it did not translate into improvements in actual task success rates or completion times. These insights provide valuable guidelines for optimizing teleoperation interfaces based on task requirements and highlight the importance of considering both cognitive demands and user experience in interface design.\n                  <\/jats:p>","DOI":"10.1145\/3785141","type":"journal-article","created":{"date-parts":[[2025,12,15]],"date-time":"2025-12-15T18:28:14Z","timestamp":1765823294000},"page":"1-42","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["A Holistic Evaluation of Teleoperation Interfaces for Robotic Manipulation"],"prefix":"10.1145","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0076-5287","authenticated-orcid":false,"given":"Shaid","family":"Hasan","sequence":"first","affiliation":[{"name":"Computer Science, University of Virginia, Charlottesville, Virginia, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4684-2823","authenticated-orcid":false,"given":"Mohammad Samin","family":"Yasar","sequence":"additional","affiliation":[{"name":"Electrical and Computer Engineering, University of Virginia, Charlottesville, Virginia, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0133-1234","authenticated-orcid":false,"given":"Tariq","family":"Iqbal","sequence":"additional","affiliation":[{"name":"University of Virginia, Charlottesville, Virginia, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2026,1,19]]},"reference":[{"key":"e_1_3_1_2_2","doi-asserted-by":"publisher","DOI":"10.1016\/0967-0661(94)00078-U"},{"issue":"1","key":"e_1_3_1_3_2","doi-asserted-by":"crossref","first-page":"6","DOI":"10.1177\/1557234X13510679","article-title":"Space telerobotics: Unique challenges to human\u2013robot collaboration in space","volume":"9","author":"Fong Terrence","year":"2013","unstructured":"Terrence Fong, Jennifer Rochlis Zumbado, Nancy Currie, Andrew Mishkin, and David L. 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Retrieved from https:\/\/arxiv.org\/abs\/2403.07869"},{"key":"e_1_3_1_100_2","doi-asserted-by":"publisher","DOI":"10.1145\/3610978.3640552"},{"key":"e_1_3_1_101_2","volume-title":"Proceedings of the 5th International Workshop on Virtual, Augmented, and Mixed Reality for HRI","author":"LeMasurier Gregory","year":"2022","unstructured":"Gregory LeMasurier, Jordan Allspaw, Murphy Wonsick, James Tukpah, Taskin Padir, Holly Yanco, and Elizabeth Phillips. 2022. Designing a user study for comparing 2D and VR human-in-the-loop robot planning interfaces. In Proceedings of the 5th International Workshop on Virtual, Augmented, and Mixed Reality for HRI."},{"key":"e_1_3_1_102_2","first-page":"335","volume-title":"Proceedings of the 18th International Symposium on Robotics Research (ISRR)","author":"Whitney David","year":"2019","unstructured":"David Whitney, Eric Rosen, Elizabeth Phillips, George Konidaris, and Stefanie Tellex. 2019. 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Retrieved from https:\/\/link.springer.com\/chapter\/10.1007\/978-3-642-29041-1_5"},{"key":"e_1_3_1_108_2","first-page":"2255","volume-title":"Proceedings of the 2012 IEEE International Conference on Robotics and Automation","author":"Ficuciello Fanny","year":"2012","unstructured":"Fanny Ficuciello, Gianluca Palli, Claudio Melchiorri, and Bruno Siciliano. 2012. Planning and control during reach to grasp using the three predominant UB hand IV postural synergies. In Proceedings of the 2012 IEEE International Conference on Robotics and Automation. 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Retrieved from https:\/\/arxiv.org\/abs\/2007.06695","DOI":"10.15607\/RSS.2020.XVI.045"},{"key":"e_1_3_1_114_2","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2022.3196158"},{"key":"e_1_3_1_115_2","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2015.7353607"},{"key":"e_1_3_1_116_2","doi-asserted-by":"crossref","first-page":"518","DOI":"10.1109\/Humanoids53995.2022.10000248","volume-title":"Proceedings of the 2022 IEEE-RAS 21st International Conference on Humanoid Robots (Humanoids)","author":"Elangovan Nathan","year":"2022","unstructured":"Nathan Elangovan, Che-Ming Chang, Ricardo V. Godoy, Felipe Sanches, Ke Wang, Patrick Jarvis, and Minas Liarokapis. 2022. Comparing human and robot performance in the execution of kitchen tasks: Evaluating grasping and dexterous manipulation skills. In Proceedings of the 2022 IEEE-RAS 21st International Conference on Humanoid Robots (Humanoids). 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