%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