%0 Journal Article
%T Fast Reinforcement Learning approach to robust optimal control of bipedal robots with Point-feet
%J International Journal of Robotics, Theory and Applications
%I K.N. Toosi University of Technology
%Z 2008-7144
%A Anjidani, Majid
%A Jahed Motlagh, Mohammad Reza
%A Fathy, Mahmood
%A Nili Ahmadabad, Majid
%D 2021
%\ 06/01/2021
%V 7
%N 1
%P -
%! Fast Reinforcement Learning approach to robust optimal control of bipedal robots with Point-feet
%K Legged robots
%K Reinforcement Learning
%K robust gait optimization
%R
%X Designing a walking gait for biped robots, that can preserve stability against a known range of disturbances, is very important in real applications. In the area of biped robots with point-feet, designing an exponentially stable walking gait with desired features has been recently done by an online reinforcement learning method called PI^2-WG. However, the designed gait might not be robust enough against disturbances. Therefore, we extend a robust version of PI^2-WG to design an exponentially stable walking gait which is robust against modeling errors/disturbances and we call it R-SPI^2-WG. It is done by minimizing the costs of worst rollouts which are generated in presence of different modeling errors/disturbances. We study the ability of the proposed method to adapt the controller of RABBIT, which is a planar biped robot with point-feet, for some robust applications. The simulation results show that the designed gaits are exponentially stable and robust against modeling errors/disturbances in a feasible range.
%U