SCANS: A Soft Gripper With Curvature and Spectroscopy Sensors for In-Hand Material Differentiation

We introduce the soft curvature and spectroscopy (SCANS) system: a versatile, electronics-free, fluidically actuated soft manipulator capable of assessing the spectral properties of objects either in hand or through pre-touch caging. This platform offers a wider spectral sensing capability than previous soft robotic counterparts. We perform a material analysis to explore optimal soft substrates for spectral sensing, and evaluate both pre-touch and in-hand performance. Experiments demonstrate explainable, statistical separation across diverse object classes and sizes (metal, wood, plastic, organic, paper, foam), with large spectral angle differences between items. Through linear discriminant analysis, we show that sensitivity in the near-infrared wavelengths is critical to distinguishing visually similar objects. These capabilities advance the potential of optics as a multi-functional sensory modality for soft robots. The complete parts list, assembly guidelines, and processing code for the SCANS gripper are accessible at: <uri xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">https://parses-lab.github.io/scans/</uri>.

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Publication Details

Journal
IEEE Robotics and Automation Letters
Published
2025-10-13
DOI
https://doi.org/10.1109/lra.2025.3620619
Primary Topic
Robot Manipulation and Learning
Type
article
Field-Weighted Citation Impact
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article

SCANS: A Soft Gripper With Curvature and Spectroscopy Sensors for In-Hand Material Differentiation

Taşkın Padır, Kristen L. Dorsey, Charles A. DiMarzio, Nathaniel Hanson et al.
IEEE Robotics and Automation Letters
Robot Manipulation and Learning
article

SCANS: A Soft Gripper With Curvature and Spectroscopy Sensors for In-Hand Material Differentiation

Taşkın Padır, Kristen L. Dorsey, Charles A. DiMarzio, Nathaniel Hanson, Austin Allison
article en

Abstract

We introduce the soft curvature and spectroscopy (SCANS) system: a versatile, electronics-free, fluidically actuated soft manipulator capable of assessing the spectral properties of objects either in hand or through pre-touch caging. This platform offers a wider spectral sensing capability than previous soft robotic counterparts. We perform a material analysis to explore optimal soft substrates for spectral sensing, and evaluate both pre-touch and in-hand performance. Experiments demonstrate explainable, statistical separation across diverse object classes and sizes (metal, wood, plastic, organic, paper, foam), with large spectral angle differences between items. Through linear discriminant analysis, we show that sensitivity in the near-infrared wavelengths is critical to distinguishing visually similar objects. These capabilities advance the potential of optics as a multi-functional sensory modality for soft robots. The complete parts list, assembly guidelines, and processing code for the SCANS gripper are accessible at: <uri xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">https://parses-lab.github.io/scans/</uri>.

IEEE Robotics and Automation LettersVol. 10(12)
Northeastern University (US)
Openalex Percentile: Top 63%
Robot Manipulation and Learning
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SCANS: A Soft Gripper With Curvature and Spectroscopy Sensors for In-Hand Material Differentiation — Taşkın Padır, Kristen L. Dorsey, et al. · IEEE Robotics and Automation Letters (2025) | TGRS Research Map | TGRS