2026-07-28 04:00 UTCOriginal source2 min readUpdated: 2026-07-28 08:53 UTC

Pose-Aware Modeling to Mitigate Pose-Related Artifacts in Tactile Gloves

A new algorithm uses hand pose data to reduce force sensing errors in flexible tactile gloves, improving minimum detectable force by up to 18.3% across multiple designs and users.

SourcearXiv RoboticsAuthor: Tianhong Catherine Yu, Ziyi Kou, Mia Huang, Taylor Niehues, Yiyue Luo, Li Guan, Dingtian Zhang

-->

[Submitted on 25 Jul 2026]

Title:Pose-Aware Modeling to Mitigate Pose-Related Artifacts in Tactile Gloves

View a PDF of the paper titled Pose-Aware Modeling to Mitigate Pose-Related Artifacts in Tactile Gloves, by Tianhong Catherine Yu and 6 other authors

View PDF HTML (experimental)

Abstract:Tactile gloves digitize contact and force during hand-object interactions, enabling robotics applications in dexterous manipulation, teleoperation, and learning from demonstration. To preserve hand dexterity and capture the nuances of natural interactions, these gloves and the integrated tactile sensors are designed to be soft, flexible, and comfortable. However, such flexible sensors are sensitive not only to contact forces but also unavoidably to hand pose changes, resulting in pose-related artifacts (PRAs). PRAs are especially problematic in the low-force range, resulting in misdetections or late-onset detections of contact, which raises the minimum detectable force (MDF) of the glove. In this work, we characterize the PRAs in relation to pose and force. Building on these insights, we introduce a glove-agnostic algorithmic framework that leverages hand pose information, which is increasingly available, to mitigate PRAs without glove modifications. Our pose-aware force estimation model augments tactile-to-force pipelines with a residual prediction branch that explicitly accounts for pose-induced sensor deformations. We validate our approach across 3 glove designs and 15 users, reducing MDF by 10.4%, 12.2%, and 18.3%, with consistent improvements across all evaluated metrics. This method provides a practical path to improving the usability of tactile gloves in data collection and diverse robotic applications.

Subjects:

Robotics (cs.RO); Human-Computer Interaction (cs.HC)

Cite as: arXiv:2607.22964 [cs.RO]

(or arXiv:2607.22964v1 [cs.RO] for this version)

https://doi.org/10.48550/arXiv.2607.22964

arXiv-issued DOI via DataCite (pending registration)

Submission history

From: Tianhong Yu [view email] [v1] Sat, 25 Jul 2026 00:12:31 UTC (4,578 KB)

Full-text links:

Access Paper:

View a PDF of the paper titled Pose-Aware Modeling to Mitigate Pose-Related Artifacts in Tactile Gloves, by Tianhong Catherine Yu and 6 other authors

View PDF

HTML (experimental)

TeX Source

view license

Current browse context:

cs.RO

new | recent | 2026-07

Change to browse by:

cs cs.HC

References & Citations

NASA ADS

Google Scholar

Semantic Scholar

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

Replicate Toggle

Replicate (What is Replicate?)

Spaces Toggle

Hugging Face Spaces (What is Spaces?)

Spaces Toggle

TXYZ.AI (What is TXYZ.AI?)