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F-TOUCH Sensor: Concurrent Geometry Perception and Multi-Axis Force Measurement

delete2021-02-15
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OA
AI
W
Wanlin Li
A
Akram Alomainy
I
Ivan Vitanov
Y
Yohan Noh
彭奇 (Peng Qi)
K
Kaspar Althoefer *
DOI:10.1109/JSEN.2020.3030631delete
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摘要

摘要

En 中文
Force and tactile sensing has experienced a surge of interest over recent decades. It conveys a range of information through physical interaction, including force, pressure, texture and vibration. Even so, existing tactile sensors have difficulty in precisely acquiring force signals to capture magnitude and direction. This is because vision-based tactile sensors, such as the popular GelSight sensor, estimate force and torque from discrete markers embedded in a compliant sensor interface and detected via image processing, resulting in force errors that are sizeable. This paper presents a novel design for a force/tactile sensor, namely F-TOUCH (Force and Tactile Optically Unified Coherent Haptics), that signifies an appreciable advance on current state-of-the-art tactile sensors. In addition to the acquisition of geometric features via the (silicone) elastomeric component at a high spatial resolution, our sensor incorporates a deformable spring-mechanism structure, allowing us to measure translational and rotational force and torque along six axes with high accuracy. The proposed sensor contains three principal components: a coated elastomer layer acting as the compliant sensing medium, spring mechanisms acting as deformable structural elements, and a camera for image capture. The camera records the deformation of the structural elements as well as the distortion of the compliant sensing medium, concurrently acquiring force and tactile information. The sensor is calibrated with the aid of a commercial ATI Industrial Automation(R) 6-axis force/torque sensor. An experimental study reveals that the F-TOUCH sensor outperforms GelSight as a force sensor.
Keyword:
Force
Tactile sensors
Force measurement
Cameras
Tactile sensing
force
torque sensor
contact sensing
vision
image processing
robotics
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期刊

IEEE Sensors Journal 封面图
IEEE Sensors Journal
IF:
4.5
论文数:
2.1W
被引数:
7.3W

机构

Q
Queen Mary University London
学者数:
2.0W
论文数: 1.5W
被引数: 327
U
university of london
学者数:
21.5W
论文数: 19.7W
被引数: 305
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