  DribbleBot (Dexterous Ball Manipulation with a Legged Robot) is a legged
robotic system that can dribble a soccer ball under the same real-world
conditions as humans (i.e., in-the-wild). We adopt the paradigm of training
policies in simulation using reinforcement learning and transferring them into
the real world. We overcome critical challenges of accounting for variable ball
motion dynamics on different terrains and perceiving the ball using
body-mounted cameras under the constraints of onboard computing. Our results
provide evidence that current quadruped platforms are well-suited for studying
dynamic whole-body control problems involving simultaneous locomotion and
manipulation directly from sensory observations.
