Shunsuke Koseki — accepted AI-conference papers

2025

Concerted Control: Modulating Joint Stiffness Using GRF for Gait Generation At Different Speeds

Shunsuke Koseki, Omid Mohseni, Dai Owaki, Mitsuhiro Hayashibe, André Seyfarth, Maziar Ahmad Sharbafi

RA-L 2025

This letter proposes a bio-inspired, simple, and easy-to-implement walking controller, termed <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Concerted Control</i>, which leverages a shared common signal to coordinate movements across multiple joints

Cited by 3 Source ↗Scholar ↗

2025

Two-stage Learning Framework Combining Joint-level Reinforcement Learning and Muscle-level Adaptation for Musculoskeletal Locomotion

Laurie Azoulay, Kyo Kutsuzawa, Shunsuke Koseki, Dai Owaki, Mitsuhiro Hayashibe

IROS 2025

Animal musculoskeletal systems are renowned for their ability to dynamically regulate stiffness and achieve energy-efficient motion. Being inspired by the biological control structure, this study presents a hybrid control framework that utilizes two-stage learning processes for body movement plannin

Cited by 0 Source ↗Scholar ↗