Digiteye: a Transparent Soft Tactile Sensor for Robust Multi-Modal Perception
 
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1
Department of Science and Technology, Hanoi University of Industry, Viet Nam
 
2
School of Mechanical and Automotive Engineering, Hanoi University of Industry, Viet Nam
 
3
Hanoi University of Industry, School of Mechanical and Automotive Engineering, Viet Nam
 
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HaUI Institute of Technology, Hanoi University of Industry, Viet Nam
 
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School of Information and Communication Technology, Hanoi University of Industry, Viet Nam
 
 
Submission date: 2025-09-30
 
 
Final revision date: 2025-11-02
 
 
Acceptance date: 2025-11-02
 
 
Online publication date: 2025-12-01
 
 
Corresponding author
Son Tien Bui   

Department of Science and Technology, Hanoi University of Industry, 298 Cau Dien str., 100000, Hanoi, Viet Nam
 
 
 
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ABSTRACT
Tactile sensing remains fundamental for enabling dexterous robotic manipulation and safe human–robot interaction. Existing visuotactile sensors often compromise either deformation depth or optical transparency, limiting their ability to capture both contact forces and external scene information. This paper presents DigitEye, a transparent soft tactile sensor with a hollow box-shaped silicone rubber skin that deforms at the centimeter scale while preserving high optical clarity. A one-shot molding process with inner-frame grooves ensures robust adhesion and modular replacement of the soft skin, while dark-blue markers embedded through CNC-machined molds enable reliable tracking under varied conditions. To validate the design, we constructed two benchmark datasets: a force-sensing dataset linking images to indentation depth and ground-truth force, and an object detection dataset of fruits under varying distances and lighting. Experimental evaluations demonstrate reliable force estimation across multiple contact geometries, together with YOLO-based recognition, achieving a precision of 0.95, a recall of 0.87, and an mAP@0.5 of 0.689. These results highlight DigitEye as a practical platform for transparent visuotactile sensing, supporting both fine-grained contact perception and safer robotic operation in unstructured environments.
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ISSN:1895-7595
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