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About

Naoto Wakatsuki is a researcher specializing in acoustic signal processing and autonomous mobile robotics, with a particular focus on self-localization systems that leverage sound-based sensing technologies. His most significant contribution is the development of low-cost acoustic beacon-based localization methods for indoor mobile robots, introduced in his most-cited work (2015, 39 citations), which cleverly combines microphone arrays, wheel odometry, and known-frequency sound beacons to achieve reliable position estimation without expensive sensor suites. Wakatsuki's research has progressively tackled real-world challenges in acoustic localization, including handling reverberant environments through iterative Bayesian filtering, evaluating the effects of phase-modulated M-sequence signals on direction-of-arrival accuracy, and characterizing TDOA estimation errors caused by microphone array motion. His more recent work pushes toward minimalist hardware solutions, demonstrating self-localization using a single acoustic channel by exploiting impulse responses and the Doppler effect — a notable step toward practical, resource-constrained robotic systems. With a cumulative citation record anchored by impactful foundational work, Wakatsuki represents a steady voice in indoor acoustic robotics. Students and researchers exploring cost-effective alternatives to LiDAR or vision-based localization will find his body of work an essential and practically grounded reference.