Katsumichi Sameshima

Papers

Total Citations

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About

Katsumichi Sameshima is a robotics researcher specializing in motion planning and autonomous navigation, with a particular focus on multi-agent systems and competitive robotics. His work bridges the gap between theoretical optimization and practical implementation, most notably through his development of a path planning framework for RoboCup soccer. In his highly cited 2014 paper, Sameshima introduced an innovative approach that integrates the Rapidly-exploring Random Tree (RRT) algorithm with Particle Swarm Optimization (PSO) to dynamically tune critical parameters, enabling agile and adaptive navigation for soccer-playing robots in real-time, adversarial environments. This contribution addresses a key challenge in robotics: balancing computational efficiency with robust performance under dynamic constraints. While his citation count reflects a focused, early-career impact, Sameshima’s work has been instrumental in advancing the capabilities of autonomous agents in competitive settings, offering a practical methodology that other researchers have built upon for similar motion planning tasks. His research continues to explore the intersection of optimization and robotics, aiming to create more intelligent and responsive systems for complex, real-world applications.