Masato Kobayashi

Kobe University, The University of Osaka, California Maritime Academy, Kobe Design University, Osaka University of Economics

论文数

18

总引用数

280

H-Index

9

关于

暂无简介。

研究焦点

Artificial intelligence18 · 280 次引用
Computer science18 · 280 次引用
Robot16 · 246 次引用
Mobile robot13 · 228 次引用
Motion planning9 · 200 次引用
Path (computing)8 · 196 次引用
Mathematics6 · 166 次引用
Control (management)8 · 154 次引用
Obstacle4 · 150 次引用
Obstacle avoidance3 · 145 次引用
Control theory (sociology)6 · 141 次引用
Constant (computer programming)2 · 115 次引用

主要成就

9
H 指数
18
论文
280
总引用数
16
篇均引用
🏆 最高被引论文
Local Path Planning: Dynamic Window Approach With Virtual Manipulators Considering Dynamic Obstacles
100 次引用 · 2022
📈 最高产年份: 2023 (6 论文)
🤝 主要合作者: 13
🏛 所属机构: Kobe University, The University of Osaka, California Maritime Academy, Kobe Design University, Osaka University of Economics

代表论文

  1. 1
    Local Path Planning: Dynamic Window Approach With Virtual Manipulators Considering Dynamic Obstacles
    100 次引用 · 2022
  2. 2
    Local Path Planning: Dynamic Window Approach With Q-Learning Considering Congestion Environments for Mobile Robot
    38 次引用 · 2023
  3. 3
    Path Planning for Mobile Robot Considering Turnabouts on Narrow Road by Deep Q-Network
    29 次引用 · 2023
  4. 4
    Bi-ACT: Bilateral Control-Based Imitation Learning via Action Chunking with Transformer
    25 次引用 · 2024
  5. 5
    Local Path Planning Method Based on Virtual Manipulators and Dynamic Window Approach for a Wheeled Mobile Robot
    15 次引用 · 2021
  6. 6
    ILBiT: Imitation Learning for Robot Using Position and Torque Information based on Bilateral Control with Transformer
    13 次引用 · 2024
  7. 7
    BSL: Navigation Method Considering Blind Spots Based on ROS Navigation Stack and Blind Spots Layer for Mobile Robot
    10 次引用 · 2023
  8. 8
    ALPHA- α and Bi-ACT Are All You Need: Importance of Position and Force Information/ Control for Imitation Learning of Unimanual and Bimanual Robotic Manipulation With Low-Cost System
    9 次引用 · 2025
  9. 9
    Remote Control Method for Mobile Robot Based on Force Feedback Generated using Collision Prediction Map
    9 次引用 · 2019
  10. 10
    Local Path Planning with Turnabouts for Mobile Robot by Deep Deterministic Policy Gradient
    7 次引用 · 2023

主要合作者

NMNaoki Motoi13 篇合著论文TNTomoaki Nakamura4 篇合著论文HTHaruo Takemura3 篇合著论文YUYuki Uranishi3 篇合著论文TBThanpimon Buamanee3 篇合著论文RMRyo Masaki2 篇合著论文HZHiroka Zushi2 篇合著论文EIEduardo Iglesius1 篇合著论文KTKazutoshi Tanaka1 篇合著论文HKHayato Kimura1 篇合著论文MHMasashi Hamaya1 篇合著论文JYJun Yamada1 篇合著论文TKTakumi Kobayashi1 篇合著论文
尚未生成