Kouchi Matsutani
Papers
2
Total Citations
47
H-Index
2
About
Kouchi Matsutani is a robotics researcher whose work focuses on enabling autonomous robot navigation using vision-based systems, particularly in human-centric environments. His primary research areas include visual navigation, semantic segmentation, and intersection detection using monocular cameras as cost-effective alternatives to expensive 3D LiDAR sensors. Matsutani’s most impactful contribution is his 2020 paper “Visual Navigation Based on Semantic Segmentation Using Only a Monocular Camera as an External Sensor,” which has garnered 38 citations. This work demonstrates how robots can navigate autonomously using a single camera, making them more practical for deployment in everyday human spaces. In a 2021 follow-up study, “Feasibility Study of Intersection Detection and Recognition Using a Single Shot Image for Robot Navigation” (9 citations), he further explored how robots can recognize and navigate complex intersections from a single image. Matsutani’s research is notable for its potential to reduce hardware costs while maintaining robust navigation capabilities, bridging the gap between advanced robotics and real-world applications. His work is particularly relevant for students and researchers interested in affordable, vision-based autonomous systems.
Research Focus
Key Achievements
Top Papers
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