Kohei Matsumoto
Papers
10
Total Citations
62
H-Index
4
About
Kohei Matsumoto is a leading researcher in service robotics, specializing in informationally structured environments, autonomous navigation, and human-robot interaction. His foundational work on "Development of ROS-TMS 5.0 for informationally structured environments" (18 citations) established a management framework that integrates robot and environmental data to enable real-time, on-demand service in daily-life settings. Matsumoto has made significant contributions to spatial perception, developing fast change-detection techniques using voxel classification and normal distributions transform (11 citations) that are critical for search-and-rescue and surveillance robots. In navigation, he pioneered learning-based and hybrid methods—including deep reinforcement learning and normalizing flows—for crowd-aware robot movement in dynamic pedestrian environments. A standout achievement is his deployment of a tour guide robot at a large theme park, leveraging Japan’s Quasi-Zenith Satellite System and 5G communications for robust outdoor localization and co-experience with visitors (7 citations). His work bridges theoretical advances in predictive state representation and real-time microprocessor control with practical, real-world applications. With over 60 total citations across his top publications, Matsumoto’s research is shaping the next generation of autonomous service robots that can safely and intelligently operate alongside people in complex, unstructured environments.
Research Focus
Key Achievements
Top Papers
- 1Development of ROS-TMS 5.0 for informationally structured environment18 citations · 2018
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- 3Quasi-Zenith Satellite System-based Tour Guide Robot at a Theme Park7 citations · 2020
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- 7Spatial change detection using normal distributions transform4 citations · 2019
- 8A Thread Speed Control Scheme for Real-Time Microprocessors3 citations · 2011
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