Kazufumi Honda
Papers
3
Total Citations
24
H-Index
2
About
Kazufumi Honda is a robotics researcher whose work centers on visual navigation and autonomous mobile robots, with a particular emphasis on human-centric environments. His primary research areas include semantic segmentation, visual odometry, and sensor fusion for robot localization and control. Honda's major contributions lie in developing practical navigation methods that enable robots to operate safely and effectively in spaces shared with pedestrians. His 2023 study on "Practical Implementation of Visual Navigation Based on Semantic Segmentation" (14 citations) addresses the critical challenge of robots performing expected actions without being affected by nearby people, introducing a semantics-based localization approach. In another notable work, "Turning at Intersections Using Virtual LiDAR Signals Obtained from a Segmentation Result" (8 citations), he innovated a control strategy where robots navigate toward target points determined by semantic information. Additionally, his research on "Improvement of Visual Odometry Based on Robust Feature Extraction Considering Semantics" (2 citations) advances the accuracy of location estimation by combining visual and IMU data. Through these contributions, Honda is advancing the reliability of autonomous robots in complex, dynamic environments.
Research Focus
Key Achievements
Top Papers
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