  A novel control & software architecture using ROS C++ is introduced for
object interception by a UAV with a mounted depth camera and no external aid.
Existing work in trajectory prediction focused on the use of off-board tools
like motion capture rooms to intercept thrown objects. The present study
designs the UAV architecture to be completely on-board capable of object
interception with the use of a depth camera and point cloud processing. The
architecture uses an iterative trajectory prediction algorithm for
non-propelled objects like a ping-pong ball. A variety of path planning
approaches to object interception and their corresponding scenarios are
discussed, evaluated & simulated in Gazebo. The successful simulations
exemplify the potential of using the proposed architecture for the on-board
autonomy of UAVs intercepting objects.
