Kiyosumi Kidono

The University of Osaka, Toyota Central Research and Development Laboratories (Japan)

Papers

Total Citations

111

H-Index

About

Kiyosumi Kidono is a researcher whose work lies at the intersection of autonomous navigation and visual simultaneous localization and mapping (SLAM). His foundational research, particularly the highly cited 2002 paper “Autonomous visual navigation of a mobile robot using a human-guided experience” (102 citations), introduced a pioneering strategy that minimizes user assistance by allowing a robot to learn environmental information through human-guided demonstrations. This approach reduces the tedious task of manual map creation, enabling more intuitive and efficient autonomous navigation. Kidono’s later work, such as “Fast Bayesian graph update for SLAM” (2022), addresses the critical need for robust and accurate localization in modern robotics by advancing visual SLAM techniques. His contributions have helped shape how robots perceive and navigate complex environments, making him a notable figure in the field. With a career spanning over two decades, Kidono’s research continues to influence the development of autonomous systems, offering practical solutions that bridge human guidance and machine autonomy.