A Convex Tactile Sensor for Isotropic Tissue Elastic Modulus Estimation Based on the Plane Contact Model

Li, Chenggang; Yan, Dengdeng; Shen, Jingjin

doi:10.1109/jsen.2019.2910289

Cited by 4 publications

(1 citation statement)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For human beings, tactile feedback is the second most important signal receptor after vision, which plays an important role in life. With the development of tactile sensor technology [209][210][211][212][213], researchers hope that robots can also have the same tactile perception ability as humans and further realize intelligence. It is a good idea to apply tactile technology to the robot alone, which can avoid the fusion of different signals and improve the processing speed of the system.…”

Section: A Tactile Feedbackmentioning

confidence: 99%

Object Detection Recognition and Robot Grasping Based on Machine Learning: A Survey

Bai

Yang

et al. 2020

IEEE Access

View full text Add to dashboard Cite

With the rapid development of machine learning, its powerful function in the machine vision field is increasingly reflected. The combination of machine vision and robotics to achieve the same precise and fast grasping as that of humans requires high-precision target detection and recognition, location and reasonable grasp strategy generation, which is the ultimate goal of global researchers and one of the prerequisites for the large-scale application of robots. Traditional machine learning has a long history and good achievements in the field of image processing and robot control. The CNN (convolutional neural network) algorithm realizes training of large-scale image datasets, solves the disadvantages of traditional machine learning in large datasets, and greatly improves accuracy, thereby positioning CNNs as a global research hotspot. However, the increasing difficulty of labeled data acquisition limits their development. Therefore, unsupervised learning, self-supervised learning and reinforcement learning, which are less dependent on labeled data, have also undergone rapid development and achieved good performance in the fields of image processing and robot capture. According to the inherent defects of vision, this paper summarizes the research achievements of tactile feedback in the fields of target recognition and robot grasping and finds that the combination of vision and tactile feedback can improve the success rate and robustness of robot grasping. This paper provides a systematic summary and analysis of the research status of machine vision and tactile feedback in the field of robot grasping and establishes a reasonable reference for future research.

show abstract

Section: A Tactile Feedbackmentioning

confidence: 99%

Object Detection Recognition and Robot Grasping Based on Machine Learning: A Survey

Bai

Yang

et al. 2020

IEEE Access

View full text Add to dashboard Cite

show abstract

Tactile sensor with an inverted V-shaped indenter for elastic tissue identification

Lü

Shen

2019

Intel Serv Robotics

View full text Add to dashboard Cite

Highly sensitive flexible modulus sensor for softness perception and clinical application

Zou¹,

Yang²,

Wang³

2022

J. Micromech. Microeng.

View full text Add to dashboard Cite

The wearable sensors for softness measuring are emerging as a solution of softness perception, which is an intrinsic function of human skin, for electronic skin and human-machine interaction. However, these wearable sensors suffer from a key challenge: the modulus of an object can not be characterized directly, which originates from the complicated transduction mechanism. To address this key challenge, we developed a flexible and wearable modulus sensor that can simultaneously measure the pressure and modulus without mutual interference. The modulus sensing was realized by merging the electrostatic capacitance response from the pressure sensor and the ionic capacitance response from the indentation sensor. Via the optimized structure, our sensor exhibits high modulus sensitivity of 1.9 × 102 in 0.06 MPa, a fast dynamic response time of 100 ms, and high mechanical robustness for over 2500 cycles. We also integrated the sensor onto a prosthetic hand and surgical probe to demonstrate its capability for pressure and modulus sensing. This work provides a new strategy for modulus measurement, which has great potential in softness sensing and medical application.

show abstract

A Convex Tactile Sensor for Isotropic Tissue Elastic Modulus Estimation Based on the Plane Contact Model

Cited by 4 publications

References 27 publications

Object Detection Recognition and Robot Grasping Based on Machine Learning: A Survey

Object Detection Recognition and Robot Grasping Based on Machine Learning: A Survey

Tactile sensor with an inverted V-shaped indenter for elastic tissue identification

Highly sensitive flexible modulus sensor for softness perception and clinical application

Contact Info

Product

Resources

About