World's Best Scientists 2026 revealed!
Toshio Fukuda

Toshio Fukuda

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Electronics and Electrical Engineering
Japan
2026
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Mechanical and Aerospace Engineering
Japan
2026

D-Index & Metrics

Mechanical and Aerospace Engineering

D-Index
83
Citations
33146
World Ranking
166
National Ranking
1

Electronics and Electrical Engineering

D-Index
83
Citations
33260
World Ranking
422
National Ranking
9

Toshio Fukuda publication distribution in Mechanical and Aerospace Engineering in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Mechanical and Aerospace Engineering in 2026. The highlighted bar marks where Toshio Fukuda sits on this spectrum.

47–56 publications: 10 scientists 57–66 publications: 23 scientists 67–76 publications: 32 scientists 77–86 publications: 62 scientists 87–96 publications: 67 scientists 97–106 publications: 91 scientists 107–116 publications: 113 scientists 117–126 publications: 115 scientists 127–136 publications: 130 scientists 137–146 publications: 140 scientists 147–156 publications: 155 scientists 157–166 publications: 132 scientists 167–176 publications: 133 scientists 177–186 publications: 130 scientists 187–196 publications: 140 scientists 197–206 publications: 115 scientists 207–216 publications: 125 scientists 217–226 publications: 117 scientists 227–236 publications: 99 scientists 237–246 publications: 92 scientists 247–256 publications: 100 scientists 257–266 publications: 95 scientists 267–276 publications: 88 scientists 277–286 publications: 77 scientists 287–296 publications: 74 scientists 297–306 publications: 74 scientists 307–316 publications: 62 scientists 317–326 publications: 70 scientists 327–336 publications: 59 scientists 337–346 publications: 58 scientists 347–356 publications: 45 scientists 357–366 publications: 44 scientists 367–376 publications: 36 scientists 377–386 publications: 41 scientists 387–396 publications: 32 scientists 397–406 publications: 23 scientists 407–416 publications: 28 scientists 417–426 publications: 27 scientists 427–436 publications: 25 scientists 437–446 publications: 23 scientists 447–456 publications: 23 scientists 457–466 publications: 20 scientists 467–476 publications: 12 scientists 477–486 publications: 24 scientists 487–496 publications: 18 scientists 497–506 publications: 12 scientists 507–516 publications: 13 scientists 517–526 publications: 21 scientists 527–536 publications: 12 scientists 537–546 publications: 8 scientists 547–556 publications: 16 scientists 557–566 publications: 3 scientists 567–576 publications: 11 scientists 577–586 publications: 6 scientists 587–596 publications: 5 scientists 597–606 publications: 6 scientists 607–616 publications: 7 scientists 617–626 publications: 7 scientists 627–636 publications: 10 scientists 637–646 publications: 4 scientists 647–656 publications: 3 scientists 657–658 publications: 2 scientists 659+ publications: 100 scientists
47 publications 659+

This scientist: 2,308 publications — 100th percentile

100% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 659 publications or more.

Toshio Fukuda D-index placement in Mechanical and Aerospace Engineering in 2026

The chart shows the D-index (discipline H-index) distribution of Mechanical and Aerospace Engineering scientists ranked by Research.com in 2026. The highlighted bar marks where Toshio Fukuda sits on this spectrum.

30 D-Index: 83 scientists 31 D-Index: 113 scientists 32 D-Index: 144 scientists 33 D-Index: 153 scientists 34 D-Index: 189 scientists 35 D-Index: 158 scientists 36 D-Index: 139 scientists 37 D-Index: 127 scientists 38 D-Index: 130 scientists 39 D-Index: 126 scientists 40 D-Index: 104 scientists 41 D-Index: 100 scientists 42 D-Index: 107 scientists 43 D-Index: 101 scientists 44 D-Index: 103 scientists 45 D-Index: 79 scientists 46 D-Index: 88 scientists 47 D-Index: 70 scientists 48 D-Index: 83 scientists 49 D-Index: 44 scientists 50 D-Index: 64 scientists 51 D-Index: 56 scientists 52 D-Index: 50 scientists 53 D-Index: 48 scientists 54 D-Index: 58 scientists 55 D-Index: 52 scientists 56 D-Index: 48 scientists 57 D-Index: 42 scientists 58 D-Index: 34 scientists 59 D-Index: 42 scientists 60 D-Index: 37 scientists 61 D-Index: 42 scientists 62 D-Index: 44 scientists 63 D-Index: 22 scientists 64 D-Index: 33 scientists 65 D-Index: 29 scientists 66 D-Index: 23 scientists 67 D-Index: 29 scientists 68 D-Index: 24 scientists 69 D-Index: 19 scientists 70 D-Index: 34 scientists 71 D-Index: 26 scientists 72 D-Index: 19 scientists 73 D-Index: 18 scientists 74 D-Index: 19 scientists 75 D-Index: 14 scientists 76 D-Index: 19 scientists 77 D-Index: 8 scientists 78 D-Index: 18 scientists 79 D-Index: 16 scientists 80 D-Index: 12 scientists 81 D-Index: 17 scientists 82 D-Index: 11 scientists 83 D-Index: 16 scientists 84 D-Index: 7 scientists 85 D-Index: 9 scientists 86 D-Index: 8 scientists 87 D-Index: 6 scientists 88 D-Index: 6 scientists 89 D-Index: 7 scientists 90 D-Index: 10 scientists 91 D-Index: 4 scientists 92 D-Index: 4 scientists 93+ D-Index: 100 scientists
30 D-Index 93+

This scientist: 83 D-Index — 95th percentile

95% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 93 D-Index or more.

Research.com Recognitions

  • 2026 - Research.com Electronics and Electrical Engineering in Japan Leader Award
  • 2026 - Research.com Mechanical and Aerospace Engineering in Japan Leader Award
  • 2025 - Research.com Electronics and Electrical Engineering in Japan Leader Award
  • 2025 - Research.com Mechanical and Aerospace Engineering in Japan Leader Award
  • 2023 - Research.com Mechanical and Aerospace Engineering in China Leader Award
  • 2022 - Research.com Mechanical and Aerospace Engineering in China Leader Award
  • 2010 - IEEE Robotics & Automation Award “For leadership and pioneering contributions to Intelligent Robotic Systems and Micro and Nano Robotic Systems.”

Overview

Toshio Fukuda is affiliated with Nagoya University in Japan and has a research focus primarily within the field of Engineering, with a significant number of publications totaling 107. Their work spans several subfields, including Biomedical Engineering, Condensed Matter Physics, Mechanical Engineering, Control and Systems Engineering, and Cell Biology.

The scientist's research topics encompass Micro and Nano Robotics, 3D Printing in Biomedical Research, Modular Robots and Swarm Intelligence, Advanced Sensor and Energy Harvesting Materials, Robotic Locomotion and Control, Advanced Materials and Mechanics, and Neuroscience and Neural Engineering. These areas highlight a multidisciplinary approach toward robotics and related technologies.

Frequent coauthors collaborating with Toshio Fukuda include Qiang Huang, Qing Shi, Huaping Wang, Tao Sun, and Karen Hawkins, indicating sustained research partnerships over time.

Key recent publications include:

  • Ionic shape-morphing microrobotic end-effectors for environmentally adaptive targeting, releasing, and sampling, 2021, Nature Communications
  • A review on microrobots driven by optical and magnetic fields, 2023, Lab on a Chip
  • Programmable aniso-electrodeposited modular hydrogel microrobots, 2022, Science Advances
  • Development of a Small-Sized Quadruped Robotic Rat Capable of Multimodal Motions, 2022, IEEE Transactions on Robotics
  • Human-Following Control of Cane-Type Walking-Aid Robot Within Fixed Relative Posture, 2021, IEEE/ASME Transactions on Mechatronics

Frequent publication venues where Toshio Fukuda's work appears are:

  • IEEE/ASME Transactions on Mechatronics
  • IEEE Robotics and Automation Letters
  • Nature Communications
  • Lab on a Chip
  • IEEE Transactions on Robotics

Toshio Fukuda is also an author of academic books, with at least one publication by Springer Nature titled Robust and Intelligent Control of a Typical Underactuated Robot published in 2023.

The scientist has been recognized with the IEEE Robotics & Automation Award in 2010, cited for leadership and pioneering contributions to Intelligent Robotic Systems and Micro and Nano Robotic Systems.

Best Publications

  • A bioinspired multilegged soft millirobot that functions in both dry and wet conditions

    Haojian Lu;Mei Zhang;Yuanyuan Yang;Qiang Huang

  • Theory and applications of neural networks for industrial control systems

    T. Fukuda;T. Shibata

  • A new type of fish-like underwater microrobot

    Shuxiang Guo;T. Fukuda;K. Asaka

  • Dynamically Reconfigurable Robotic System

    Toshio Fukuda;Seiya Nakagawa

  • Shape Sensing Techniques for Continuum Robots in Minimally Invasive Surgery: A Survey

    Chaoyang Shi;Xiongbiao Luo;Peng Qi;Tianliang Li

  • Assembly of nanodevices with carbon nanotubes through nanorobotic manipulations

    T. Fukuda;F. Arai;L. Dong

  • Cellular robotic system (CEBOT) as one of the realization of self-organizing intelligent universal manipulator

    T. Fukuda;Y. Kawauchi

  • Mechanism and swimming experiment of micro mobile robot in water

    T. Fukuda;A. Kawamoto;F. Arai;H. Matsuura

  • Sliding-Mode Velocity Control of Mobile-Wheeled Inverted-Pendulum Systems

    Jian Huang;Zhi-Hong Guan;Takayuki Matsuno;Toshio Fukuda

  • Micro manipulation based on micro physics-strategy based on attractive force reduction and stress measurement

    F. Arai;D. Ando;T. Fukuda;Y. Nonoda

  • Mechatronics - "What Is It, Why, and How?" An editorial

    Fumio Harashima;Masayoshi Tomizuka;Toshio Fukuda

  • Feedback Control of an Omnidirectional Autonomous Platform for Mobile Service Robots

    Keigo Watanabe;Yamato Shiraishi;Spyros G. Tzafestas;Jun Tang

  • Self-tuning fuzzy modeling with adaptive membership function, rules, and hierarchical structure based on genetic algorithm

    Koji Shimojima;Toshio Fukuda;Yasuhisa Hasegawa

  • A brachiating robot controller

    J. Nakanishi;T. Fukuda;D.E. Koditschek

  • Swing and locomotion control for a two-link brachiation robot

    F. Saito;T. Fukuda;F. Arai

  • An exoskeletal robot for human shoulder joint motion assist

    K. Kiguchi;K. Iwami;M. Yasuda;K. Watanabe

  • Structure decision method for self organising robots based on cell structures-CEBOT

    T. Fukuda;S. Nakagawa;Y. Kawauchi;M. Buss

  • Approach to the dynamically reconfigurable robotic system

    Toshio Fukuda;Seiya Nakagawa

  • A pso-based mobile robot for odor source localization in dynamic advection-diffusion with obstacles environment: theory, simulation and measurement

    W. Jatmiko;K. Sekiyama;T. Fukuda

  • Human-Walking-Intention-Based Motion Control of an Omnidirectional-Type Cane Robot

    K. Wakita;Jian Huang;Pei Di;K. Sekiyama

  • Distributed Autonomous Robotic Systems

    Hajime Asama;Toshio Fukuda;Tamio Arai;Isao Endo

Frequent Co-Authors

Fumihito Arai
Fumihito Arai University of Tokyo
Yasuhisa Hasegawa
Yasuhisa Hasegawa Nagoya University
Qiang Huang
Qiang Huang Beijing Institute of Technology
Kazuhiro Kosuge
Kazuhiro Kosuge University of Hong Kong
Michio Homma
Michio Homma Nagoya University
Lixin Dong
Lixin Dong City University of Hong Kong
Takanori Shibata
Takanori Shibata National Institute of Advanced Industrial Science and Technology
Kazuo Kiguchi
Kazuo Kiguchi Kyushu University
Xinkai Chen
Xinkai Chen Shibaura Institute of Technology
Shuxiang Guo
Shuxiang Guo Southern University of Science and Technology

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