AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。
[Submitted on 21 Oct 2026] Title:Tactile-Based Robotic Manipulation: From Mechanics-Driven to Data-Driven Perspectives View a PDF of the paper titled Tactile-Based Robotic Manipulation: From Mechanics-Driven to Data-Driven Perspectives, by Jingyi Xiang and 2 other authors View PDF HTML (experimental) Abstract:Tactile sensing provides robots with direct access to physical interactions at the contact interface, making it a critical modality for robust and dexterous manipulation. Over the past several decades, tactile-based manipulation research has evolved from mechanics-driven approaches, which explicitly interpret tactile signals through contact mechanics and task-specific reasoning, to data-driven approaches that learn tactile representations and manipulation policies directly from data. This paper reviews the development of tactile-based manipulation from these two complementary perspectives. We first introduce the fundamentals of tactile sensing, and then review, from a mechanics-driven perspective, how those signals form manipulation-relevant state representations and subsequently influence the robot action. We then examine the recent advances in data-driven tactile manipulation, covering imitation learning, reinforcement learning, vision-language-action models, and predictive models. Finally, we discuss open challenges and future opportunities toward scalable, generalizable, and robust tactile-enabled robotic systems. Comments: 30 pages. Author accepted manuscript. Posted with permission from the Annual Review of Control, Robotics, and Autonomous Systems, Volume 10; copyright 2027 the author(s), this https URL. Published version: this https URL Subjects: Robotics (cs.RO) Cite as: arXiv:2610.30438 [cs.RO] (or arXiv:2610.30438v1 [cs.RO] for this version) https://doi.org/10.48550/arXiv.2610.30438 arXiv-issued DOI via DataCite (pending registration) Related DOI: https://doi.org/10.1146/annurev-control-032125-030330 DOI(s) linking to related resources Submission history From: Jingyi Xiang [view email] [v1] Wed, 21 Oct 2026 20:49:25 UTC (82 KB) Full-text links: Access Paper: View a PDF of the paper titled Tactile-Based Robotic Manipulation: From Mechanics-Driven to Data-Driven Perspectives, by Jingyi Xiang and 2 other authors View PDF HTML (experimental) TeX Source view license Additional Features Audio Summary Current browse context: cs.RO new | recent | 2026-10 Change to browse by: cs References & Citations SciX 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?)