Gakuto Masuyama
Papers
6
Total Citations
55
H-Index
5
About
Gakuto Masuyama is a robotics researcher whose work focuses on enabling mobile robots to perceive and navigate dynamic, real-world environments. His primary research areas include computer vision, target tracking, and autonomous navigation, with a particular emphasis on robust perception under challenging conditions. Masuyama’s major contributions center on developing vision-based systems that allow robots to reliably follow humans and detect moving objects, even when faced with occlusion, illumination changes, or crowded spaces. His most cited work, “Occlusion handling for a target-tracking robot with a stereo camera” (19 citations), introduces a method that fuses color and disparity data to maintain tracking continuity. Another key paper, “Human following with a mobile robot based on combination of disparity and color images” (11 citations), demonstrates a system robust to sunlight and lighting variations. Masuyama has also tackled navigation in dynamic environments, proposing a method that leverages pedestrian flow to help robots move through crowds. His work on a compact range image sensor for robot hands further showcases his interest in practical, real-time sensing solutions. With a cumulative impact of over 50 citations, Masuyama’s research provides foundational techniques for mobile robots operating in unpredictable, human-centered settings.
Research Focus
Key Achievements
Top Papers
- 1Occlusion handling for a target-tracking robot with a stereo camera19 citations · 2018
- 2
- 3Detecting Moving Objects Using Optical Flow with a Moving Stereo Camera8 citations · 2016
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