  In this paper, we address the task of interacting with dynamic environments
where the changes in the environment are independent of the agent. We study
this through the context of trapping a moving ball with a UR5 robotic arm. Our
key contribution is an approach to utilize a static planner for dynamic tasks
using a Dynamic Planning add-on; that is, if we can successfully solve a task
with a static target, then our approach can solve the same task when the target
is moving. Our approach has three key components: an off-the-shelf static
planner, a trajectory forecasting network, and a network to predict robot's
estimated time of arrival at any location. We demonstrate the generalization of
our approach across environments. More information and videos at
https://mlevy2525.github.io/DynamicAddOn.
