Model predictive control of legged and humanoid robots: models and algorithms
Publication loaded PDF Page 1 / 18 fullscreen remove_circle_outline add_circle_outline search group_add more_horiz get_app info list link ADVANCED ROBOTICS 2023, VOL. 37, NO. 5, 298–315 https://doi.org/10.1080/01691864.2023.2168134 SURVEY PAPER Model predictive control of legged and humanoid robots: models and algorithms Sotaro Katayama a , Masaki Murooka b and Yuichi Tazaki c a Graduate School of Informatics, Kyoto University, Kyoto, Japan; b CNRS-AIST JRL, IRL, Tsukuba, Japan; c Graduate School of Engineering, Kobe University, Kobe, Japan ABSTRACT Model predictive control (MPC) of legged and humanoid robotic systems has been an active research topic in the past decade. While MPC for robotic systems has a long history, its paradigm such as problem formulations and algorithms has changed along with the recent drastic progress in robot hardware, computational processors, and algorithms. This survey paper reviews recent progress on MPC for le
Explore this link on the map →