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（利用腿式机器人进行灵巧控球）是一种能在与人类相同的真实世界条件（即野外）下运球的腿式机器人系统。我们采用强化学习在仿真中训练策略并将其迁移到现实世界的范式。我们克服了关键挑战，包括在不同地形上解释可变球的运动动力学，以及在机载计算约束下使用机身安装的摄像头感知球。我们的结果表明，当前的四足平台非常适合研究涉及直接从感官观察进行同时行走和操控的动态全身控制问题。