An Object Recognition Grasping Approach Using Proximal Policy Optimization With YOLOv5

An Object Recognition Grasping Approach Using Proximal Policy Optimization With YOLOv5

Aiming at the problems of traditional grasping methods for mobile manipulators, such as single application scenarios, low accuracy, and complex grasping tasks, this paper proposes an object recognition grasping approach using Proximal Policy Optimization (PPO) with You Only Look Once v5 (YOLOv5), wh...

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Bibliographic Details
Main Authors: Qingchun Zheng, Zhi Peng, Peihao Zhu, Yangyang Zhao, Ran Zhai, Wenpeng Ma
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Access
Subjects:
Deep reinforcement learning
manipulator
object grasping
proximal policy optimization
YOLOv5
Online Access:https://ieeexplore.ieee.org/document/10217816/

Internet

https://ieeexplore.ieee.org/document/10217816/

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