Robustly maintaining balance on two legs is an important challenge for humanoid robots. The
work presented in this book represents a contribution to this area. It investigates efficient
methods for the decision-making from internal sensors about whether and where to step several
improvements to efficient whole-body postural balancing methods and proposes and evaluates a
novel method for efficient recovery step generation leveraging human examples and
simulation-based reinforcement learning.
