Yuji Hasegawa

Papers

Total Citations

H-Index

About

Yuji Hasegawa is a robotics researcher whose work sits at the intersection of autonomous decision-making, motion control, and legged locomotion systems. His research addresses some of the most demanding challenges in practical robotics: enabling machines to operate intelligently under real-world constraints of limited computing power and sensor fidelity. One of Hasegawa's notable contributions is the development of the Sampling Real-Time Q-MDP Value Method, applied to dynamic soccer robot scenarios, which advances fast, adaptive decision-making for autonomous agents operating in unpredictable environments. This work demonstrates a practical pathway for deploying probabilistic planning algorithms on resource-constrained robotic platforms. Hasegawa has also contributed to the field of legged robotics through time-optimal control methods for quadruped walking robots, extending established manipulator control theory — particularly Bobrow's foundational work — into the more complex domain of body-supported locomotion systems. While his citation counts remain modest — reflecting either the specialized nature of his contributions or early-career positioning at the time of publication — his research tackles genuinely difficult engineering problems that underpin modern autonomous and biomimetic robotics. Students exploring robot decision-making or quadruped locomotion will find his methodological approaches a useful entry point into these technically rich subfields.