Isao Takami

Papers

Total Citations

H-Index

About

Isao Takami is a robotics researcher whose work focuses on intelligent control systems for mobile robots, particularly in challenging environments with limited sensor data. His most-cited paper, "Neural network trajectory tracking of tracked mobile robot" (2019, 18 citations), addresses a fundamental problem in robotics: how to achieve precise trajectory tracking when a robot is equipped with only three binary sensors that return simple 0 or 1 signals. Takami's key contribution lies in developing an online neural network controller capable of learning and adapting in real-time, overcoming the severe constraints imposed by such impoverished sensory input. This work demonstrates his broader research interests in neural network-based control, sensor-limited navigation, and autonomous mobile robotics. While his citation count reflects a focused, emerging career, the innovative nature of his approach—solving a seemingly impossible tracking problem with minimal sensing—has established him as a creative problem-solver in the field. His research holds practical implications for low-cost robotic systems in agriculture, search-and-rescue, and other domains where sophisticated sensors are impractical.