UniGrasp: Learning a Unified Model to Grasp With Multifingered Robotic Hands-Reference-Cited by-同舟云学术

UniGrasp: Learning a Unified Model to Grasp With Multifingered Robotic Hands

Published:2020-04 Issue:2 Volume:5 Page:2286-2293
ISSN:2377-3766
Container-title:IEEE Robotics and Automation Letters
language:
Short-container-title:IEEE Robot. Autom. Lett.

Author:

Shao Lin^ORCID,Ferreira Fabio^ORCID,Jorda Mikael,Nambiar Varun,Luo Jianlan,Solowjow Eugen^ORCID,Ojea Juan Aparicio,Khatib Oussama,Bohg Jeannette^ORCID

Funder

JD.com American Technologies Corporation

SAIL-JD AI Research Initiative

International Center for Advanced Communication Technologies

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Artificial Intelligence,Control and Optimization,Computer Science Applications,Computer Vision and Pattern Recognition,Mechanical Engineering,Human-Computer Interaction,Biomedical Engineering,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/7083369/8932682/08972562.pdf?arnumber=8972562

Cited by 64 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. Learning accurate and efficient three-finger grasp generation in clutters with an auto-annotated large-scale dataset;Robotics and Computer-Integrated Manufacturing;2025-02

2. DiPGrasp: Parallel Local Searching for Efficient Differentiable Grasp Planning;IEEE Robotics and Automation Letters;2024-10

3. The improved force/position hybrid control system for multi joint humanoid multi fingered dexterous hand;Journal of Mechanical Science and Technology;2024-08

4. Learning a Contact Potential Field for Modeling the Hand-Object Interaction;IEEE Transactions on Pattern Analysis and Machine Intelligence;2024-08

5. Open X-Embodiment: Robotic Learning Datasets and RT-X Models : Open X-Embodiment Collaboration⁰;2024 IEEE International Conference on Robotics and Automation (ICRA);2024-05-13