Legged locomotion holds the premise of universal mobility, a critical capability for many real-
world robotic applications. Both model-based and learning-based approaches have …

Robust locomotion control depends on accurate state estimations. However, the sensors of
most legged robots can only provide partial and noisy observations, making the estimation …

Legged robots are physically capable of traversing a wide range of challenging
environments, but designing controllers that are sufficiently robust to handle this diversity …

Achieving versatile robot locomotion requires motor skills that can adapt to previously
unseen situations. We propose a multi-expert learning architecture (MELA) that learns to …

Learning controllers that reproduce legged locomotion in nature has been a longtime goal in
robotics and computer graphics. While yielding promising results, recent approaches are not …

While most recent advancements in legged robot control have been driven by model-free
reinforcement learning, we explore the potential of differentiable simulation. Differentiable …

Legged robots are a class of biologically inspired robots that use articulated leg
mechanisms for locomotion. Legged motion is very complex and requires specialized …

Legged locomotion is one of the most versatile forms of mobility. However, despite the
importance of legged locomotion and the large number of legged robotics studies, no biped …

Reproducing the diverse and agile locomotion skills of animals has been a longstanding
challenge in robotics. While manually-designed controllers have been able to emulate many …

Parkour is a grand challenge for legged locomotion, even for quadruped robots, requiring
active perception and various maneuvers to overcome multiple challenging obstacles …