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About

Kenichi Furuhashi is a robotics and autonomous systems researcher whose work spans agricultural automation, mobile robot navigation, and state estimation. His research addresses some of the most pressing challenges in deploying autonomous robots in unstructured, real-world environments — from orchards and lakeshores to sloped terrain. Furuhashi's most impactful contribution, "Visual-Inertial RGB-D SLAM With Encoders for a Differential Wheeled Robot" (2021, 20 citations), advances robust state estimation for wheeled robots by integrating encoder data with visual-inertial odometry, improving reliability where existing approaches frequently fail in practice. His broader portfolio reflects a consistent drive to make autonomous navigation practical and accessible across diverse agricultural settings, including GNSS-free orchard navigation using CNNs and RGB-D cameras, LiDAR-based SLAM in chestnut orchards, and slope-aware robotic mowing using low-cost dual-frequency GNSS systems. Beyond ground robots, Furuhashi has pioneered novel agricultural platforms, notably developing a small electric robot boat capable of autonomously mowing aquatic weeds — a creative solution to lake ecosystem management. His work on persimmon posture detection using convolutional neural networks further demonstrates his versatility in applying machine vision to food production automation. Together, his research makes a meaningful contribution to the future of smart, autonomous agriculture.