Papers
20
Total Citations
217
H-Index
8
About
Shunsuke Shigaki is a pioneering researcher at the intersection of bioinspired robotics, chemical plume tracing, and computational neuroscience, whose work has fundamentally advanced how autonomous systems navigate complex olfactory environments. Drawing inspiration from insect behavior—particularly the silk moth—Shigaki has developed sophisticated algorithms that enable robots to locate odor sources in turbulent, real-world conditions. His most celebrated contribution, the Time-Varying Moth-Inspired Algorithm (2017, 52 citations), established a robust framework for chemical plume tracing across diverse environments, becoming a cornerstone reference in the field. Beyond algorithm design, Shigaki bridges biology and engineering through inventive experimental tools, including the innovative 3-DOF servosphere system for studying untethered insect locomotion. His application of deep inverse reinforcement learning and information-theoretic modeling to decode insect search strategies reflects his commitment to uncovering the neural and behavioral principles underlying adaptive navigation. With contributions spanning bioactuators, bioinspired robotic feet, and multimodal odor-source localization, Shigaki's interdisciplinary portfolio—accumulating over 180 citations—demonstrates a rare ability to translate biological insights into transformative robotic technologies, offering meaningful advances in gas leak detection, search-and-rescue operations, and our broader understanding of animal cognition.
Research Focus
Key Achievements
Top Papers
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- 7Animal-in-the-loop system to investigate adaptive behavior15 citations · 2018
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