Tactile-Guided Robot Learning: From Representation Learning to Foundation Models

原文：Tactile-Guided Robot Learning: From Representation Learning to Foundation Models

作者：Kiyanoush Nazari, Luchen Li, Haoshu Fang, Nima Fazeli, Zhibin Li, Fumiya Iida, Thomas George Thuruthel

来源：arXiv cs.RO（机器人）

正文

Computer Science > Robotics

arXiv:2610.20134v1 (cs)

[Submitted on 14 Oct 2026]

Title:Tactile-Guided Robot Learning: From Representation Learning to Foundation Models

Authors:Kiyanoush Nazari, Luchen Li, Haoshu Fang, Nima Fazeli, Zhibin Li, Fumiya Iida, Thomas George Thuruthel

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Abstract:Tactile sensing is becoming central to robust, adaptive, and dexterous robotic manipulation. Beyond its traditional role in contact detection and reactive control, touch is increasingly used to learn transferable representations, condition manipulation policies, and support embodied physical reasoning. Yet existing surveys largely emphasize tactile hardware and perception, leaving the rapid shift toward learning-based tactile manipulation insufficiently synthesized. This paper reviews tactile-guided skill learning from a learning-centric perspective, organized by the functional role of touch across the learning and control pipeline. We examine tactile representation and policy learning, tactile foundation models, predictive and adaptive control, and generalization across objects, tasks, sensors, embodiments, and simulation-to-real transfer. Across these directions, we identify common design principles and remaining challenges in learning transferable physical representations, integrating semantic reasoning with contact-level control, and scaling tactile learning across heterogeneous data and hardware. Finally, we outline emerging directions toward tactile foundation and world models that can predict, reason about, and adapt physical interactions. Together, this review characterizes the transition of touch from a task-specific feedback signal toward a core modality for general-purpose embodied intelligence. An accompanying database of the reviewed literature and associated resources is available at this https URL.

Subjects:

Robotics (cs.RO)

Cite as:

arXiv:2610.20134 [cs.RO]

(or

arXiv:2610.20134v1 [cs.RO] for this version)

https://doi.org/10.48550/arXiv.2610.20134

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机器人

由「前沿雷达」于 2026-10-14 采集。正文取自原文页面，已保留出处链接。标题与正文版权归原作者所有。