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
  • [1] Evolvable Motion-planning Method using Deep Reinforcement Learning
    Nishi, Kaichiro
    Nakasu, Nobuaki
    2021 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA 2021), 2021, : 4079 - 4085
  • [2] An Experimental Study for Algorithm of Finding for Resident-Tracking Robot System
    Sugimoto, Masashi
    Uchida, Ryunosuke
    Tsuzuki, Shinji
    Hirano, Masatsugu
    Yoshioka, Takashi
    Nonaka, Shogo
    2020 INTERNATIONAL SYMPOSIUM ON COMMUNITY-CENTRIC SYSTEMS (CCS), 2020,
  • [3] Event-triggered reconfigurable reinforcement learning motion-planning approach for mobile robot in unknown dynamic environments
    Sun, Huihui
    Zhang, Changchun
    Hu, Chunhe
    Zhang, Junguo
    ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2023, 123
  • [4] A continuation method for motion-planning problems
    Chitour, Y
    ESAIM-CONTROL OPTIMISATION AND CALCULUS OF VARIATIONS, 2006, 12 (01) : 139 - 168
  • [5] A SIMPLE MOTION-PLANNING ALGORITHM FOR GENERAL ROBOT MANIPULATORS
    LOZANOPEREZ, T
    IEEE JOURNAL OF ROBOTICS AND AUTOMATION, 1987, 3 (03): : 224 - 238
  • [6] Motion Planning for Human-Robot Collaboration based on Reinforcement Learning
    Yu, Tian
    Chang, Qing
    2022 IEEE 18TH INTERNATIONAL CONFERENCE ON AUTOMATION SCIENCE AND ENGINEERING (CASE), 2022, : 1866 - 1871
  • [7] Effective metrics for multi-robot motion-planning
    Atias, Aviel
    Solovey, Kiril
    Salzman, Oren
    Halperin, Dan
    INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH, 2018, 37 (13-14): : 1741 - 1759
  • [8] Effective Metrics for Multi-Robot Motion-Planning
    Atias, Aviel
    Solovey, Kiril
    Halperin, Dan
    ROBOTICS: SCIENCE AND SYSTEMS XIII, 2017,
  • [9] Randomised MPC-based Motion-Planning for Mobile Robot Obstacle Avoidance
    Brooks, Alex
    Kaupp, Tobias
    Makarenko, Alexei
    ICRA: 2009 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION, VOLS 1-7, 2009, : 397 - 402
  • [10] Motion-planning and pose-tracking based rendezvous and docking with a tumbling target
    Zhou, Bang-Zhao
    Liu, Xiao-Feng
    Cai, Guo-Ping
    ADVANCES IN SPACE RESEARCH, 2020, 65 (04) : 1139 - 1157
12345