Papers
4
Total Citations
64
H-Index
4
About
Jirou Nitta is a leading researcher in autonomous mobile robotics, with a focus on enabling robots to navigate safely and intelligently in complex, human-populated environments. His work spans deep learning for robot navigation, large-scale mapping, and human-aware path planning. Nitta’s most influential contribution is the GOSELO framework, which uses reactive neural networks for goal-directed obstacle and self-localization mapping, a paper that has garnered 35 citations for addressing the critical challenge of policy generalization in robot learning. He is also known for pioneering long-term, real-world validation of autonomous systems, as demonstrated by his highly cited 2017 study where a mobile robot operated continuously for an entire day in a science museum—a landmark experiment that tested the limits of navigation without human-motion models. His research on generating 3D fundamental maps via large-scale SLAM and graph-based optimization, focused on road center lines, has advanced practical mapping for autonomous vehicles. By integrating pedestrian information into path planning, Nitta has developed methods that allow robots to anticipate and respect human movement rules, moving beyond static obstacle maps. His work is essential reading for anyone interested in deploying robots that coexist with people in dynamic, everyday settings.
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