We are interested in studying sports with robots and starting with the problem of intercepting a projectile moving toward a robot manipulator equipped with a shield. To successfully perform this task, the robot needs to (i) detect the incoming projectile, (ii) predict the projectile's future motion, (iii) plan a minimum-time rapid trajectory that can evade obstacles and intercept the projectile, and (iv) execute the planned trajectory. These four steps must be performed under the manipulator's dynamic limits and extreme time constraints (<350ms in our setting) to successfully intercept the projectile. In addition, we want these trajectories to be smooth to reduce the robot's joint torques and the impulse on the platform on which it is mounted. To this end, we propose a kinodynamic motion planning framework that preprocesses smooth trajectories offline to allow real-time collision-free executions online. We present an end-to-end pipeline along with our planning framework, including perception, prediction, and execution modules. We evaluate our framework experimentally in simulation and show that it has a higher blocking success rate than the baselines. Further, we deploy our pipeline on a robotic system comprising an industrial arm (ABB IRB-1600) and an onboard stereo camera (ZED 2i), which achieves a 78% success rate in projectile interceptions.

翻译：我们致力于研究体育中的机器人技术，并从拦截朝向配备防护盾的机器人臂运动的抛射体这一问题入手。为成功完成此任务，机器人需要：(i) 检测来袭抛射体，(ii) 预测抛射体的未来运动轨迹，(iii) 规划一条能够避开障碍物并拦截抛射体的最小时间快速轨迹，以及 (iv) 执行所规划的轨迹。这四个步骤必须在机器人臂的动态限制和严格时间约束（在我们的设置中时间小于350毫秒）下完成，以成功拦截抛射体。此外，我们希望这些轨迹平滑，以减小机器人关节扭矩及其安装平台的冲击力。为此，我们提出了一种运动动力学运动规划框架，该框架通过离线预处理平滑轨迹，实现实时的在线无碰撞执行。我们展示了包括感知、预测和执行模块在内的端到端管道及其规划框架。我们在仿真中通过实验评估了该框架，并证明其拦截成功率高于基线方法。进一步，我们将该管道部署在由工业臂（ABB IRB-1600）和机载立体相机（ZED 2i）组成的机器人系统上，实现了78%的抛射体拦截成功率。