AI 服务暂时不可用，以下为来源正文，待恢复后补全翻译。
[Submitted on 11 Sep 2026] Title:MR-GLi: Mixed Reality-Based Gripper-Linked Overlays for Underwater Robot Arm Teleoperation via Bilateral Control View a PDF of the paper titled MR-GLi: Mixed Reality-Based Gripper-Linked Overlays for Underwater Robot Arm Teleoperation via Bilateral Control, by Masashi Sasago and 2 other authors View PDF HTML (experimental) Abstract:Visual torque feedback supports underwater bilateral teleoperation, but the benefit of mixed reality (MR) over conventional monitor presentation remains unclear. We present MR-GLi, an MR interface that spatially registers a reaction torque indicator and wrist-camera image to the robot gripper. Twenty participants performed lift and pick-and-place tasks with rigid and compliant objects in a counterbalanced within-subject comparison with a 2D monitor, using identical visual-feedback content and four-channel bilateral control. MR-GLi provided gripper-linked access to visual feedback while maintaining a similar level of torque-regulation performance to the 2D monitor. Subjective evaluation further indicated reduced perceived burden associated with shifting attention between the workspace and visual feedback. These results demonstrate the feasibility of gripper-linked MR overlays for underwater bilateral teleoperation and highlight the importance of considering information access in addition to task performance. Additional material: this https URL Subjects: Robotics (cs.RO) Cite as: arXiv:2609.16041 [cs.RO] (or arXiv:2609.16041v1 [cs.RO] for this version) https://doi.org/10.48550/arXiv.2609.16041 arXiv-issued DOI via DataCite Submission history From: Masato Kobayashi [view email] [v1] Fri, 11 Sep 2026 23:11:06 UTC (24,999 KB) Full-text links: Access Paper: View a PDF of the paper titled MR-GLi: Mixed Reality-Based Gripper-Linked Overlays for Underwater Robot Arm Teleoperation via Bilateral Control, by Masashi Sasago and 2 other authors View PDF HTML (experimental) TeX Source view license Current browse context: cs.RO new | recent | 2026-09 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar Loading... Data provided by: Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Code, Data and Media Associated with this Article alphaXiv Toggle alphaXiv (What is alphaXiv?) Links to Code Toggle CatalyzeX Code Finder for Papers (What is CatalyzeX?) DagsHub Toggle DagsHub (What is DagsHub?) GotitPub Toggle Gotit.pub (What is GotitPub?) Huggingface Toggle Hugging Face (What is Huggingface?) ScienceCast Toggle ScienceCast (What is ScienceCast?) Demos Demos Replicate Toggle Replicate (What is Replicate?) Spaces Toggle Hugging Face Spaces (What is Spaces?) Spaces Toggle TXYZ.AI (What is TXYZ.AI?) Related Papers Recommenders and Search Tools Link to Influence Flower Influence Flower (What are Influence Flowers?) Core recommender toggle CORE Recommender (What is CORE?) Author Venue Institution Topic About arXivLabs arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs. Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)