A study for Motion-Planning Method Resident-tracking Robot based on Reinforcement Learning

被引：0
|
作者：
Sugimoto, Masashi [1 ]
Yoshioka, Takashi [2 ]
Ishii, Kohei [3 ]
Nonaka, Shogo [4 ]
Deguchi, Mikio [5 ]
Tsuzuki, Shinji [1 ]
Hiran, Masatsugu [6 ]
机构：
[1] Electrical and Electronic Engineering Course, Ehime University, Division of Electrical and Electronic Engineering and Computer Science, 3 Bunkyo-cho, Matsuyama City, Ehime Pref.,790-8577, Japan
[2] National Institute of Technology, Kagawa College, Department of Electrical and Computer Engineering, 355 Chokushi-cho, Takamatsu City, Kagawa Pref.,761-8058, Japan
[3] National Institute of Technology, Kagawa College., Department of Electro-Mechanical Systems Engineering, 355 Chokushi-cho, Takamatsu City, Kagawa Pref.,761-8058, Japan
[4] National Institute of Technology, Tsuyama College, Department of Integrated Science and Technology, 624-1 Numa, Tsuyama City, Okayama Pref.,790-8577, Japan
[5] National Institute of Technology, Niihama College, Department of Electronics and Control Engineering, 7-1 Yakumo-cho, Niihama City, Ehime Pref.,790-8580, Japan
[6] National Institute of Technology, Niihama College, Department of Electrical Engineering and Information Science, 7-1 Yakumo-cho, Niihama City, Ehime Pref.,792-8580, Japan
来源：
MHS 2019 - 30th 2019 International Symposium on Micro-NanoMechatronics and Human Science | 2019年
关键词：
D O I：
9249075
中图分类号：
学科分类号：
摘要：
8
引用
收藏
相关论文
共 50 条
  • [21] Motion planning of differential driven robot based on tracking
    Liu Y.-B.
    Jiang Y.-Y.
    Kongzhi yu Juece/Control and Decision, 2023, 38 (09): : 2529 - 2536
  • [22] Mobile Robot Path Planning Method Based on Deep Reinforcement Learning Algorithm
    Meng, Haitao
    Zhang, Hengrui
    JOURNAL OF CIRCUITS SYSTEMS AND COMPUTERS, 2022, 31 (15)
  • [23] Robot Search Path Planning Method Based on Prioritized Deep Reinforcement Learning
    Yanglong Liu
    Zuguo Chen
    Yonggang Li
    Ming Lu
    Chaoyang Chen
    Xuzhuo Zhang
    International Journal of Control, Automation and Systems, 2022, 20 : 2669 - 2680
  • [24] Robot Search Path Planning Method Based on Prioritized Deep Reinforcement Learning
    Liu, Yanglong
    Chen, Zuguo
    Li, Yonggang
    Lu, Ming
    Chen, Chaoyang
    Zhang, Xuzhuo
    INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS, 2022, 20 (08) : 2669 - 2680
  • [25] A review of mobile robot motion planning methods: from classical motion planning workflows to reinforcement learning-based architectures
    Dong, Lu
    He, Zichen
    Song, Chunwei
    Sun, Changyin
    JOURNAL OF SYSTEMS ENGINEERING AND ELECTRONICS, 2023, 34 (02) : 439 - 459
  • [26] A review of mobile robot motion planning methods:from classical motion planning workflows to reinforcement learning-based architectures
    DONG Lu
    HE Zichen
    SONG Chunwei
    SUN Changyin
    JournalofSystemsEngineeringandElectronics, 2023, 34 (02) : 439 - 459
  • [27] Distributed safe reinforcement learning for multi-robot motion planning
    Lu, Yang
    Guo, Yaohua
    Zhao, Guoxiang
    Zhu, Minghui
    2021 29TH MEDITERRANEAN CONFERENCE ON CONTROL AND AUTOMATION (MED), 2021, : 1209 - 1214
  • [28] 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,
  • [29] Causal deconfounding deep reinforcement learning for mobile robot motion planning
    Tang, Wenbing
    Wu, Fenghua
    Lin, Shang-wei
    Ding, Zuohua
    Liu, Jing
    Liu, Yang
    He, Jifeng
    KNOWLEDGE-BASED SYSTEMS, 2024, 303
  • [30] Optimal Robot Motion Planning in Constrained Workspaces Using Reinforcement Learning
    Rousseas, Panagiotis
    Bechlioulis, Charalampos P.
    Kyriakopoulos, Kostas J.
    2020 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS), 2020, : 6917 - 6922
12345