H. Yabushita

Papers

Total Citations

H-Index

About

H. Yabushita is a robotics researcher whose work spans the critical intersection of autonomous navigation, localization reliability, and sensing technology. His primary research areas include human-aware robot navigation in crowded environments, robust localization systems, and advanced ground-penetrating radar (GPR) for detection. Yabushita’s most impactful contribution addresses the fundamental challenge of robot movement in densely populated spaces. His highly cited 2021 paper, "Robot Navigation Based on Predicting of Human Interaction," proposes a paradigm shift from treating humans as mere obstacles to modeling the reciprocal impact of a robot’s approach on human behavior, a crucial insight for real-world deployment. This work has garnered 19 citations, reflecting its relevance to the growing field of social robotics. Earlier, he contributed to localization reliability with a 2015 study on detecting Monte Carlo Localization (MCL) failure using logistic regression (12 citations), a practical method for preventing catastrophic pose estimation errors. Notably, his earlier 2005 work on 3D ground adaptive synthetic aperture radar for landmine detection (8 citations) demonstrates a versatile engineering capability, applying signal processing to create high-resolution underground images for humanitarian demining. Yabushita’s research is characterized by a pragmatic focus on solving real-world deployment problems, from crowded streets to buried hazards.