Vision-Based Tactile Sensing for an Omni-Adaptive Soft Finger

Xudong Han1; Sheng Liu1; Fang Wan2; Chaoyang Song3

10.1109/ICDL55364.2023.10364455

2023

IEEE International Conference on Development and Learning (ICDL)

978-1-6654-7076-6

2023 IEEE International Conference on Development and Learning (ICDL)

331-338

9-11 Nov. 2023

Macau, China

345 E 47TH ST, NEW YORK, NY 10017 USA

IEEE

Vision-based tactile sensing provides a novel solution to robotic proprioception using visual information to infer physical interaction on the contact surface. In this paper, we leveraged the omni-adaptive capability of a soft finger with differential stiffness by adding a monocular camera at its bottom to track its spatial deformation while interacting with objects. We modeled this soft finger's physical interaction and measured the stiffness distribution through experiments. The camera captured the soft finger's deformation when interacting with probes for different contact forces and positions. Using a neural network modified from AlexNet, we proposed a preliminary estimation model of the contact force and position using the captured images. The results show that the proposed method can achieve an accuracy of 90% for position estimation and a normalized root mean squared error of 3.4% for force estimation, showing the reliability and robustness of the proposed sensing method.

Soft Robotics Tactile Sensing Machine Vision Omni-adaptation Robot Learning

第一 ; 共同第一 ; 通讯

英语

EI ; CPCI-S

Shenzhen Key Laboratory of Intelligent Robotics and Flexible Manufacturing, Shenzhen Science and Technology Innovation Commission["JCYJ20220818100417038","SGDX20220530110804030"]

Behavioral Sciences ; Computer Science ; Robotics

Behavioral Sciences ; Computer Science, Artificial Intelligence ; Robotics

WOS:001172928700053

20240415433292

Cameras ; Learning algorithms ; Machine learning ; Mean square error ; Robot vision

Artificial Intelligence:723.4 ; Machine Learning:723.4.2 ; Vision:741.2 ; Photographic Equipment:742.2 ; Mathematical Statistics:922.2 ; Materials Science:951

IEEE

1.Shenzhen Key Lab of Intelligent Robotics & Flexible Manufacturing, Southern University of Science and Technology, Shenzhen, China
2.School of Design, Southern University of Science and Technology, Shenzhen, China
3.Mechanical and Energy Engineering, Southern University of Science and Technology, Shenzhen, China

Xudong Han,Sheng Liu,Fang Wan,et al. Vision-Based Tactile Sensing for an Omni-Adaptive Soft Finger[C]. 345 E 47TH ST, NEW YORK, NY 10017 USA:IEEE,2023:331-338.