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#tactile-sensing

6 curated events
papersTODAY 04:00 UTC

Language-Guided Representation Learning for Cross-Sensor Material Recognition

A new arXiv paper proposes using language guidance to learn material representations that transfer across different vision-based tactile sensors. Because each sensor produces distinct readings of the same material, the approach aims to close that gap by grounding learned features in shared language descriptions. The work targets robotic touch perception, where properties such as softness and texture are difficult to recover from vision alone.

robotics/tactile-sensing/representation-learning/arxiv
papersTODAY 04:00 UTC

Bench2Dex Benchmark Targets Visuo-Tactile Bimanual Dexterous Manipulation

Researchers introduce Bench2Dex, a benchmark for evaluating bimanual dexterous manipulation that combines visual and tactile sensing. The work addresses the lack of standardized tactile hardware designs across dexterous hands, which vary in finger structure, contact surfaces, and sensor layout. It aims to make performance comparisons across different hand platforms more consistent.

robotics/benchmark/tactile-sensing/dexterous-manipulation
papersTODAY 04:00 UTC

Compact ML Models Classify Affective Touch in Soft Interactive Companion

Researchers describe an end-to-end pipeline for recognizing touch gestures on a plush companion robot, whose soft body and spread-out tactile sensors complicate reliable detection. The work covers the design of small machine-learning models along with embedded validation to confirm they run effectively on the device itself. The abstract is truncated, so full details of the methods and results are not yet available.

affective-computing/tactile-sensing/embedded-ml/robotics
papersTODAY 04:00 UTC

SlipSense: Multimodal Tactile Learning for Low-Latency, Generalized Slip Detection

Researchers introduce SlipSense, a multimodal tactile framework for detecting object slip during robotic dexterous manipulation. The work emphasizes measuring detection latency precisely and testing how well the approach transfers across different hardware platforms, areas the authors say prior systems handle poorly. It is presented as an arXiv preprint in the cs.AI and cs.LG categories.

robotics/tactile-sensing/multimodal/arxiv
papersSEP 10 04:00 UTC

TaMeSo-bot Combines Tactile Memory and Soft Wrist for Robust Object Insertion

Researchers have introduced TaMeSo-bot, a soft robotic system that stores and retrieves touch-based experience to support contact-rich manipulation tasks. By pairing a masked encoding approach with a compliant soft wrist, the system aims to handle uncertainty in tasks such as inserting keys or other objects. The paper is available on arXiv with cross-listings in the AI and machine learning categories.

robotics/soft-robotics/tactile-sensing/manipulation