  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.
