Robot multi-action cooperative grasping strategy based on deep reinforcement learning

被引:0
|
作者
He, Huiteng [1 ]
Zhou, Yong [1 ]
Hu, Kaixiong [1 ]
Li, Weidong [2 ]
机构
[1] School of Transportation and Logistics Engineering, Wuhan University of Technology, Wuhan,430063, China
[2] School of Mechanical Engineering, University of Shanghai for Science and Technology, Shanghai,200093, China
关键词
Project supported by the National Natural Science Foundation; China;
D O I
10.13196/j.cims.2023.0280
中图分类号
学科分类号
摘要
引用
收藏
页码:1789 / 1797
相关论文
共 50 条
  • [41] A Hierarchical Multi-Action Deep Reinforcement Learning Method for Dynamic Distributed Job-Shop Scheduling Problem With Job Arrivals
    Huang, Jiang-Ping
    Gao, Liang
    Li, Xin-Yu
    IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, 2025, 22 : 2501 - 2513
  • [42] A Hierarchical Multi-Action Deep Reinforcement Learning Method for Dynamic Distributed Job-Shop Scheduling Problem With Job Arrivals
    Huang, Jiang-Ping
    Gao, Liang
    Li, Xin-Yu
    IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, 2025, 22 : 2501 - 2513
  • [43] Reinforcement Learning Control for Robot Arm Grasping Based on Improved DDPG
    Qi, Guangjun
    Li, Yuan
    2021 PROCEEDINGS OF THE 40TH CHINESE CONTROL CONFERENCE (CCC), 2021, : 4132 - 4137
  • [44] A Cooperative Charging Control Strategy for Electric Vehicles Based on Multiagent Deep Reinforcement Learning
    Yan, Linfang
    Chen, Xia
    Chen, Yin
    Wen, Jinyu
    IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2022, 18 (12) : 8765 - 8775
  • [45] A Hierarchical-Based Learning Approach for Multi-Action Intent Recognition
    Hollinger, David
    Pollard, Ryan S.
    Schall Jr, Mark C.
    Chen, Howard
    Zabala, Michael
    SENSORS, 2024, 24 (23)
  • [46] Multi-time scale cooperative voltage control strategy of a distribution network based on hierarchical deep reinforcement learning
    Qi, Xianglong
    Chen, Jian
    Zhao, Haoran
    Zhang, Wen
    Zhang, Keyu
    Dianli Xitong Baohu yu Kongzhi/Power System Protection and Control, 2024, 52 (18): : 53 - 64
  • [47] Deep Reinforcement Learning for Motion Planning in Human Robot cooperative Scenarios
    Nicola, Giorgio
    Ghidoni, Stefano
    2021 26TH IEEE INTERNATIONAL CONFERENCE ON EMERGING TECHNOLOGIES AND FACTORY AUTOMATION (ETFA), 2021,
  • [48] Decentralized Control of Multi-Robot System in Cooperative Object Transportation Using Deep Reinforcement Learning
    Zhang, Lin
    Sun, Yufeng
    Barth, Andrew
    Ma, Ou
    IEEE ACCESS, 2020, 8 : 184109 - 184119
  • [49] Multi-Agent Deep Reinforcement Learning-Based Multi-Objective Cooperative Control Strategy for Hybrid Electric Vehicles
    Gan, Jiongpeng
    Li, Shen
    Lin, Xianke
    Tang, Xiaolin
    IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2024, 73 (08) : 11123 - 11135
  • [50] An improved frontier-based robot exploration strategy combined with deep reinforcement learning
    Wang, Rui
    Zhang, Jie
    Lyu, Ming
    Yan, Cheng
    Chen, Yaowei
    ROBOTICS AND AUTONOMOUS SYSTEMS, 2024, 181