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About

Yoichi Shiraishi is a robotics researcher whose work bridges autonomous mobility, sensor fusion, and digital twin technologies. His primary research areas include hexapod robot locomotion, robotic lawn mower autonomy, and machine learning-based environmental sensing. Shiraishi’s major contributions lie in developing control and estimation methods for outdoor robotic systems. He created a simulator and walking analysis for hexapod robots, tackling the complex challenge of multi-leg coordination. More recently, he has pioneered the use of random forest algorithms and shallow neural networks to estimate lawn grass lengths and ground conditions for robotic lawn mowers, integrating these into Digital Twin and Virtual Twin frameworks for autonomous driving. His most-cited works, including “Development of Simulator and Analysis of Walking for Hexapod Robots” and “Estimation of Lawn Grass Lengths based on Random Forest Algorithm,” each have garnered 6 citations, demonstrating steady interest from the robotics community. By applying machine learning to real-world outdoor robotics—from hexapods to lawn care—Shiraishi advances the practical deployment of autonomous systems in unstructured environments, making his research valuable for students and engineers working on field robotics and smart agriculture.