arXiv Machine Learning June 25, 2026 By Dexter R. Shepherd, Nicolas Herzig, Phil Husbands, Andrew Philippides, Chris Johnson, William Kimbell

A 3D-Printable Dataset for Fair Testing and Comparisons of Tactile Sensors

Read the original on arXiv Machine Learning →

arXiv:2606. 25886v1 Announce Type: cross Abstract: Existing texture datasets for tactile sensing primarily consist of sensor readings from a specific sensor interacting with available surfaces/objects rather than describing the textures themselves, limiting fair comparison between tactile sensors and hindering reproducible research.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

benchmarks

arXiv AI

Jul 1

UniTac: A Unified Multimodal Model for Cross-Sensor Tactile Understanding and Generation

arXiv:2606. 31451v1 Announce Type: cross Abstract: Unified multimodal models (UMMs) have shown great promise in integrating understanding and generation across diverse modalities.

By Jiahang Tu, Fengyu Yang, Chenyang Ma, Xihang Yu, Ziyao Zeng, Shaokai Wu, Hanbin Zhao, Zhi Tao, Chao Zhang, Hui Qian, Alex Wong

multimodal benchmarks safety

arXiv Machine Learning

Jun 9

Dense Force Estimation with an Event-based Optical Tactile Sensor

arXiv:2606. 09451v1 Announce Type: cross Abstract: Humans rely on spatially dense, geometry and force-aware tactile feedback at high temporal resolution for dexterous manipulation.

By Agis Politis, Ren\'e Zurbr\"ugg, Valentina Cavinato

robotics

arXiv AI

Jul 1

RCT: A Robot-Collected Touch-Vision-Language Dataset for Tactile Generalization

arXiv:2606. 31694v1 Announce Type: cross Abstract: For robots manipulating open-world objects, tactile representations must generalize to unseen materials.

By Jingbo He, Michael F\"arber, Roberto Calandra

rag robotics multimodal

arXiv Machine Learning

Jun 15

More with LESS -- Local Scene Representations for Tactile Imaging

arXiv:2606. 14344v1 Announce Type: new Abstract: Tactile imaging seeks to reconstruct the internal structure of soft objects through touch sensing, with applications in medical diagnosis and robotic manipulation.

By Zohar Rimon, Elisei Shafer, Tal Tepper, Daniel Kozin, Alon Malka, Roy Holland, Aviv Tamar

robotics

arXiv Machine Learning

Aug 6

Tactus: Open-Vocabulary Object Recognition from Low-Cost Pressure Arrays

arXiv:2608. 04043v1 Announce Type: new Abstract: Resistive pressure arrays are the cheapest and most widely shipped tactile sensors, yet tactile representation learning has concentrated on optical sensors that image a deforming gel.

By Abdul Basit Tonmoy

benchmarks

arXiv Machine Learning

Jul 16

Tactile Modality Fusion for Vision-Language-Action Models

arXiv:2603. 14604v2 Announce Type: replace-cross Abstract: We propose TacFiLM, a lightweight modality-fusion approach that integrates visual-tactile signals into vision-language-action (VLA) models.

By Charlotte Morissette, Amin Abyaneh, Wei-Di Chang, Anas Houssaini, David Meger, Hsiu-Chin Lin, Jonathan Tremblay, Gregory Dudek

robotics fine-tuning multimodal

Related stories

UniTac: A Unified Multimodal Model for Cross-Sensor Tactile Understanding and Generation

Dense Force Estimation with an Event-based Optical Tactile Sensor

RCT: A Robot-Collected Touch-Vision-Language Dataset for Tactile Generalization

More with LESS -- Local Scene Representations for Tactile Imaging

Tactus: Open-Vocabulary Object Recognition from Low-Cost Pressure Arrays

Tactile Modality Fusion for Vision-Language-Action Models