Papers

35

Total Citations

548

H-Index

15

About

Teruo Fujii is a pioneering researcher in robotics, specializing in adaptive control systems, multi-robot coordination, and autonomous navigation. His most influential work centers on developing neural network-based controllers for underwater and mobile robots, notably the Self-Organizing Neural-Net-Controller System (SONCS), which enables real-time adaptation to dynamic environments. Fujii’s contributions to multi-robot teleoperation and collision avoidance are equally significant; he introduced the LOCISS (Locally Communicable Infrared Sensory System) and multilayered reinforcement learning frameworks that allow robot swarms to autonomously avoid obstacles and cooperate in tasks like inspection. His 2002 paper on neural network adaptation for underwater robots has garnered 51 citations, while his work on multilayered reinforcement learning for collision avoidance has reached 50 citations. Fujii also advanced human-robot interaction through Internet-based teleoperation systems, enabling remote control of multiple robots. His research on self-organizing collective robots with morphogenesis in vertical planes showcases his innovative approach to swarm robotics. With over 20 highly cited papers, Fujii’s work has profoundly influenced adaptive robotics, multi-agent systems, and human-robot collaboration, making him a key figure in the field.

Research Focus

Key Achievements

15
H-Index
35
Papers
548
Total Citations
16
Avg Citations/Paper
🏆 Most Cited Paper
Neural network system for online controller adaptation and its application to underwater robot
51 citations · 2002
📈 Most Prolific Year: 2002 (12 Papers)
🤝 Key Collaborators: 37
🏛 Institutions: RIKEN, Tokyo University of Science, The University of Tokyo, Institute of Physical and Organic Chemistry

Top Papers

  1. 1
  2. 2
  3. 3
  4. 4
  5. 5
  6. 6
  7. 7
  8. 8
  9. 9
  10. 10

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago