Koichi Mizutani
Papers
8
Total Citations
63
H-Index
4
About
Koichi Mizutani is a researcher specializing in acoustic signal processing, mobile robot localization, and sensor-based navigation systems. His work sits at the intersection of robotics and acoustics, with a particular focus on developing practical, low-cost methods for indoor positioning using sound. Mizutani's most influential contribution is his self-localization framework for mobile robots using acoustic beacons and microphone arrays, which has garnered 39 citations since its 2015 publication. This work established a foundational approach combining wheel odometry, direction-of-arrival estimation, and known acoustic sources to enable reliable robot positioning without expensive hardware. He has continued refining this research thread, incorporating iterative Bayesian filtering for robustness in reverberant environments and exploring single-channel ranging techniques exploiting the Doppler effect and impulse responses. Beyond navigation, Mizutani has demonstrated creative breadth through biomimetic research, including the development of artificial lips for automated trombone performance, and applied wireless networking work involving self-repositioning robotic access points. His investigations into M-sequence signal parameters and TDOA estimation under motion further reflect a rigorous, systems-level approach to acoustic sensing. Collectively, his research contributes meaningful practical tools for the growing field of acoustically-aware autonomous robotics.
Research Focus
Key Achievements
Top Papers
- 1Self-localization method for mobile robot using acoustic beacons39 citations · 2015
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- 6Estimation of Distance to Wall Surface using Omnidirectional Speaker3 citations · 2019
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