  Previous studies have successfully demonstrated agile and robust locomotion
in challenging terrains for quadrupedal robots. However, the bipedal locomotion
mode for quadruped robots remains unverified. This paper explores the
adaptation of a learning framework originally designed for quadrupedal robots
to operate blind locomotion in biped mode. We leverage a framework that
incorporates Adversarial Motion Priors with a teacher-student policy to enable
imitation of a reference trajectory and navigation on tough terrain. Our work
involves transferring and evaluating a similar learning framework on a
quadruped robot in biped mode, aiming to achieve stable walking on both flat
and complicated terrains. Our simulation results demonstrate that the trained
policy enables the quadruped robot to navigate both flat and challenging
terrains, including stairs and uneven surfaces.
