A Sensory Soft Robotic Gripper Capable of Learning-Based Object Recognition and Force-Controlled Grasping-Reference-Cited by-同舟云学术

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A Sensory Soft Robotic Gripper Capable of Learning-Based Object Recognition and Force-Controlled Grasping

Published:2022 Issue: Volume: Page:1-11
ISSN:1545-5955
Container-title:IEEE Transactions on Automation Science and Engineering
language:
Short-container-title:IEEE Trans. Automat. Sci. Eng.

Author:

Zhou Zhanfeng¹^ORCID,Zuo Runze¹,Ying Binbin²,Zhu Junhui³^ORCID,Wang Yong³,Wang Xin⁴,Liu Xinyu¹^ORCID

Affiliation:

1. Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, Canada

2. Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA

3. School of Electronic and Information Engineering, Suzhou University of Science and Technology, Suzhou, China

4. Department of Mechanical and Aerospace Engineering, Jilin University, Changchun, China

Funder

Natural Sciences and Engineering Research Council of Canada

Canada Foundation for Innovation

University of Toronto

Mitacs Canada (Summer Research Scholarship to R

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/8856/4358066/09999176.pdf?arnumber=9999176

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2. Electronic skin with shape sensing and Bending-Insensitive pressure sensing for soft robotic grippers object recognition;Measurement;2024-07

3. Review of machine learning in robotic grasping control in space application;Acta Astronautica;2024-07

4. Kinesthetic-based In-Hand Object Recognition with an Underactuated Robotic Hand;2024 IEEE International Conference on Robotics and Automation (ICRA);2024-05-13

5. Visual Feedback Control of an Underactuated Hand for Grasping Brittle and Soft Foods;2024 IEEE International Conference on Robotics and Automation (ICRA);2024-05-13

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