A 3-Stage Machine Learning-Based Novel Object Grasping Methodology-Reference-Cited by-同舟云学术

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A 3-Stage Machine Learning-Based Novel Object Grasping Methodology

Published:2020 Issue: Volume:8 Page:74216-74236
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Janse Van Vuuren Jacques^ORCID,Tang Liqiong,Al-Bahadly Ibrahim^ORCID,Arif Khalid Mahmood^ORCID

Funder

Massey University Manawatū, New Zealand

Richard and Mary Earle Technology Trust, the Ken and Elizabeth Powell Bursary

Massey University Foundation, New Zealand

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science

Link

http://xplorestaging.ieee.org/ielx7/6287639/8948470/09064503.pdf?arnumber=9064503

Cited by 5 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Enhanced precision in robot arm positioning: A nonlinear damping approach for flexible joint manipulators;IET Control Theory & Applications;2024-06-22

2. Machine Learning-Based Deformation Estimation for Grasping 3D Soft Objects;2024 IEEE 18th International Conference on Advanced Motion Control (AMC);2024-02-28

3. RANET: A Grasp Generative Residual Attention Network for Robotic Grasping Detection;International Journal of Control, Automation and Systems;2022-11-03

4. Prediction of Robot Grasp Robustness using Artificial Intelligence Algorithms;Tehnicki vjesnik - Technical Gazette;2022-02-05

5. A Benchmarking Platform for Learning-Based Grasp Synthesis Methodologies;Journal of Intelligent & Robotic Systems;2021-06-03

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