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.

翻译：DribbleBot（运用四腿机器人的巧妙球类操控）是一种能够在与人类相同的真实环境下（即野外）运动智能。我们采用了在仿真中训练，然后将策略转移到真实世界中的强化学习范例。我们克服了考虑不同地形上的变化球运动动力学以及使用机载摄像头感知球体的约束条件下的问题。我们的结果证明，目前的四足平台非常适合研究涉及从感官观察中同时运用整体动态控制的动态问题。