Hybrid Robotic Grasping With a Soft Multimodal Gripper and a Deep Multistage Learning Scheme-Reference-Cited by-同舟云学术

Hybrid Robotic Grasping With a Soft Multimodal Gripper and a Deep Multistage Learning Scheme

Published:2023-06 Issue:3 Volume:39 Page:2379-2399
ISSN:1552-3098
Container-title:IEEE Transactions on Robotics
language:
Short-container-title:IEEE Trans. Robot.

Author:

Liu Fukang¹^ORCID,Sun Fuchun²^ORCID,Fang Bin²^ORCID,Li Xiang³^ORCID,Sun Songyu⁴,Liu Huaping²^ORCID

Affiliation:

1. Carnegie Mellon University, Pittsburgh, PA, USA

2. Department of Computer Science and Technology, Tsinghua University, Beijing, China

3. Department of Automation, Tsinghua University, Beijing, China

4. University of California, Los Angeles, CA, USA

Funder

Major Project of the New Generation of Artificial Intelligence of China

National Natural Science Foundation of China

Tsinghua University

Department of Computer Science and Technology

China Joint Research Center for Industrial Intelligence and Internet of Things

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/8860/10144918/10037764.pdf?arnumber=10037764

Reference68 articles.

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3. Generative Attention Learning: a “GenerAL” framework for high-performance multi-fingered grasping in clutter

4. Asymmetric Actor Critic for Image-Based Robot Learning

5. Cloud-based robot grasping with the google object recognition engine

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