Work

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

Year: 2025

Type: article

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:https://parses-lab.github.io/scans/.

Source: IEEE Robotics and Automation Letters

DOI: 10.1109/lra.2025.3620619

Authors: Nathaniel Hanson, Austin Allison, Charles DiMarzio, Taşkn Padr, Kristen L. Dorsey

Institution: Northeastern University

Language: English

Topic: Soft Robotics and Applications

Subfield: Biomedical Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: green

Funder: National Science Foundation

Award: FW-HTF-RL: Co-worker Robots to Impact Seafood Processing (CRISP): Designs, Tools and Methods for Enhanced Worker Experience