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About

M. Sekiguchi is a robotics and artificial intelligence researcher whose career has centered on the development of intelligent control systems for autonomous and remotely operated robots. Best known for pioneering work in neural network-based robot behavior control, Sekiguchi's 1990 paper "Mobile Robot Control by a Structured Hierarchical Neural Network" stands as a landmark contribution to the field, accumulating 105 citations and establishing foundational principles for using hierarchical neural architectures to govern complex robotic movement and environmental response. This work, later refined through multihierarchical and dual-hierarchical network approaches across subsequent publications, demonstrated a sustained commitment to evolving more sophisticated and adaptive control frameworks. Beyond autonomous navigation, Sekiguchi made a notable practical contribution in disaster robotics with the 2004 development of a pneumatic artificial rubber muscle-driven robot designed to operate construction machinery in post-disaster environments — a timely and impactful innovation that earned 58 citations and addressed critical safety challenges for human workers. Earlier work in 1992 on self-supervised reinforcement learning further highlighted an interest in machines capable of discovering effective behaviors independently. Across more than a decade of research, Sekiguchi's contributions span foundational theory and real-world application, making meaningful advances in intelligent robotics and human-safe automation.