Yuki Matsumoto

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About

Yuki Matsumoto is a robotics researcher specializing in autonomous navigation and obstacle avoidance for mobile robots. Their key contributions focus on enabling robots to autonomously identify and enter narrow paths—a critical challenge in real-world environments like warehouses, disaster zones, or domestic spaces. In their most-cited work, "A Study on Autonomous Entering into Narrow Path Using a Mobile Robot" (2018, 5 citations), Matsumoto developed a fuzzy logic-based system that allows compact wheel robots, such as the ZUMO, to detect obstacles via sensors, execute avoidance behaviors, and safely navigate into confined spaces. This approach bridges the gap between theoretical path planning and practical robotic movement, offering a lightweight, sensor-driven solution for small-scale robots. While their citation count is modest, the work demonstrates a focused, applied methodology that has influenced subsequent studies in narrow-path navigation and fuzzy control systems. Matsumoto’s research is particularly valuable for students and engineers interested in low-cost, autonomous robotic systems that must operate in cluttered or constrained environments, highlighting the importance of sensor integration and behavior-based control in real-world robotics.