Isao Todo
Papers
13
Total Citations
39
H-Index
3
About
Isao Todo is a pioneering researcher in the field of robotic manipulation, with a career dedicated to enabling robots to interact intelligently with their environments. His key research areas include neural network-based control, multi-sensor fusion, and the challenging domain of deformable object manipulation. Todo’s major contributions lie in developing learning algorithms that allow robots to handle non-rigid materials, such as flexible beams, and to integrate visual and force/torque sensor data for precise contact tasks. His most cited work, "Coordinated Control of Two Direct-Drive Robots Using Neural Networks" (1994, 8 citations), established a foundation for cooperative robotic control. He further advanced the field with studies on impedance control and stereo vision-based servoing for object grasping. Notably, his 2005 development of an electromagnetic tactile sensor for three-axis force sensing represents a significant achievement in miniaturized sensor technology for robot fingers. Though his citation counts are modest, Todo’s work is highly specialized and foundational for researchers tackling real-world robotic challenges, particularly in manufacturing and life-support applications where adaptability to deformable objects is critical.
Research Focus
Key Achievements
Top Papers
- 1Coordinated Control of Two Direct-Drive Robots Using Neural Networks8 citations · 1994
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- 3Neural Network-Based Learning Impedance Control for a Robot.4 citations · 2001
- 4Stereo Vision-Based Robot Servoing Control for Object Grasping.3 citations · 2001
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