Shinichi Yamada

Tokyo Institute of Technology, Musashi University

Papers

Total Citations

H-Index

About

Shinichi Yamada is a robotics researcher whose work bridges evolutionary computation and autonomous vehicle control. His research focuses on two key areas: evolutionary behavior learning for robots and path tracking control for articulated vehicles. In his most cited work, "Speedup of evolutionary behavior learning with crossover depending on the usage frequency of a node" (2003, 4 citations), Yamada introduced a novel heuristic for genetic programming that accelerates online robot behavior learning by prioritizing crossover operations based on how frequently nodes are used during execution. This approach demonstrated significant speed improvements in experimental robot learning tasks. His second notable contribution, "Path tracking controller for a tractor with multiple trailers" (2002, 2 citations), addresses the challenging problem of controlling articulated vehicles with multiple trailers in industrial settings. Yamada proposed a control system that ensures rear trailer safety while maintaining accurate path tracking—a critical concern for autonomous industrial vehicles. Though his citation counts are modest, Yamada's work represents foundational contributions to two distinct robotics domains: evolutionary learning optimization and articulated vehicle control, demonstrating versatility in addressing both software-based learning and hardware-level control challenges.