Hideyuki AKIBA

Papers

Total Citations

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About

Hideyuki Akiba’s research centers on nonlinear control theory, with a particular focus on finite-time stabilization, mechanical systems, and reinforcement learning-based feedback design for mobile robotics. His work bridges rigorous mathematical control frameworks with practical autonomous systems. In his 2012 study, Akiba demonstrated that Nakamura’s local homogeneous controller, grounded in control Lyapunov functions, is effective for finite-time position control of one-link mechanical systems modeled by discontinuous differential equations—a contribution that addresses challenges in precise, time-critical robotic actuation. Expanding into autonomous navigation, his 2014 paper introduced a semi-global feedback control design method for mobile robots operating in unknown planar environments at unknown destinations. By integrating reinforcement learning with optimal action-value functions, Akiba’s approach enables the construction of a semi-global control Lyapunov function without requiring prior environmental knowledge. While his citation counts (2 per paper) reflect a focused, emerging impact, his work offers foundational insights for researchers working on robust, learning-based control in uncertain settings. Akiba’s contributions are particularly valuable for students and engineers exploring the intersection of Lyapunov theory, finite-time convergence, and adaptive robotics.