RGBGrasp: Image-Based Object Grasping by Capturing Multiple Views During Robot arm Movement With Neural Radiance Fields-Reference-Cited by-同舟云学术

RGBGrasp: Image-Based Object Grasping by Capturing Multiple Views During Robot arm Movement With Neural Radiance Fields

Published:2024-06 Issue:6 Volume:9 Page:6012-6019
ISSN:2377-3766
Container-title:IEEE Robotics and Automation Letters
language:
Short-container-title:IEEE Robot. Autom. Lett.

Author:

Liu Chang¹^ORCID,Shi Kejian²^ORCID,Zhou Kaichen³^ORCID,Wang Haoxiao⁴^ORCID,Zhang Jiyao¹^ORCID,Dong Hao¹^ORCID

Affiliation:

1. National Key Laboratory for Multimedia Information Processing, Center on Frontiers of Computing Studies, School of Computer Science, Peking University, Beijing, China

2. The Chinese University of Hong Kong, Hong Kong

3. Oxford University, Oxford, U.K.

4. Tianjin University of Technology, Tianjin, China

Funder

National Natural Science Foundation of China

National Youth Talent Support Program

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/7083369/10504377/10517376.pdf?arnumber=10517376

Reference37 articles.

1. Grasp Pose Detection in Point Clouds

2. PointNetGPD: Detecting Grasp Configurations from Point Sets

3. Recent Advancements in Learning Algorithms for Point Clouds: An Updated Overview

4. Single image 3D object detection and pose estimation for grasping

5. MonoGraspNet: 6-DoF Grasping with a Single RGB Image

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