2010 - IEEE Robotics & Automation Award “For leadership and pioneering contributions to Intelligent Robotic Systems and Micro and Nano Robotic Systems.”
Toshio Fukuda mostly deals with Robot, Control theory, Artificial intelligence, Control engineering and Mobile robot. The Robot study combines topics in areas such as Simulation and Decision model. His study in Control theory is interdisciplinary in nature, drawing from both Brachiation and Motion control.
His Artificial intelligence study frequently links to other fields, such as Computer vision. The various areas that Toshio Fukuda examines in his Control engineering study include Control system, Stability, Telerobotics, Task and Teleoperation. He has included themes like Actuator and Trajectory in his Mobile robot study.
His main research concerns Robot, Artificial intelligence, Nanotechnology, Control theory and Control engineering. Robot and Simulation are commonly linked in his work. The concepts of his Artificial intelligence study are interwoven with issues in Machine learning and Computer vision.
His Nanotechnology research includes themes of Cantilever, Nano- and Scanning electron microscope. His Control theory research focuses on Control theory and Actuator. His research integrates issues of Control system and Control in his study of Control engineering.
His scientific interests lie mostly in Nanotechnology, Robot, Biomedical engineering, Artificial intelligence and Control theory. His studies deal with areas such as Tissue engineering, Microfiber and Scanning electron microscope as well as Nanotechnology. Toshio Fukuda combines subjects such as Motion, Human–computer interaction, Simulation and Cane with his study of Robot.
His Biomedical engineering research incorporates elements of Stent, Fractal, Lobules of liver and Dura mater. Robotics is the focus of his Artificial intelligence research. His Control theory research integrates issues from Gait and Mechanism.
His primary areas of investigation include Nanotechnology, Robot, Artificial intelligence, Microfluidics and Tissue engineering. His Nanotechnology research incorporates themes from Microfiber, Cantilever and Scanning electron microscope. His Robot research includes elements of Control engineering, Cognition, Simulation and Trajectory.
His study focuses on the intersection of Simulation and fields such as Control theory with connections in the field of Swing. His research integrates issues of Motion and Mobile robot in his study of Trajectory. His research in Artificial intelligence intersects with topics in Human–computer interaction and Computer vision.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Expression Status of p16 Protein Is Associated with Human Papillomavirus Oncogenic Potential in Cervical and Genital Lesions
Takaaki Sano;Tetsunari Oyama;Kenji Kashiwabara;Toshio Fukuda.
American Journal of Pathology (1998)
Theory and applications of neural networks for industrial control systems
T. Fukuda;T. Shibata.
IEEE Transactions on Industrial Electronics (1992)
A new type of fish-like underwater microrobot
Shuxiang Guo;T. Fukuda;K. Asaka.
IEEE-ASME Transactions on Mechatronics (2003)
Neuro-fuzzy control of a robotic exoskeleton with EMG signals
K. Kiguchi;T. Tanaka;T. Fukuda.
IEEE Transactions on Fuzzy Systems (2004)
Dynamically reconfigurable robotic system
Toshio Fukuda;Seiya Nakagawa.
international conference on robotics and automation (1988)
Assembly of nanodevices with carbon nanotubes through nanorobotic manipulations
T. Fukuda;F. Arai;L. Dong.
Proceedings of the IEEE (2003)
Cellular robotic system (CEBOT) as one of the realization of self-organizing intelligent universal manipulator
T. Fukuda;Y. Kawauchi.
international conference on robotics and automation (1990)
Micro manipulation based on micro physics-strategy based on attractive force reduction and stress measurement
F. Arai;D. Ando;T. Fukuda;Y. Nonoda.
intelligent robots and systems (1995)
Complications associated with transcatheter arterial embolization for hepatic tumors.
I Sakamoto;N Aso;K Nagaoki;Y Matsuoka.
Self-tuning fuzzy modeling with adaptive membership function, rules, and hierarchical structure based on genetic algorithm
Koji Shimojima;Toshio Fukuda;Yasuhisa Hasegawa.
Fuzzy Sets and Systems (1995)
Profile was last updated on December 6th, 2021.
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