  In this work, a novel, end-to-end motion planning method is proposed for
quadrotor navigation in cluttered environments. The proposed method circumvents
the explicit sensing-reconstructing-planning in contrast to conventional
navigation algorithms. It uses raw depth images obtained from a front-facing
camera and directly generates local motion plans in the form of smooth motion
primitives that move a quadrotor to a goal by avoiding obstacles. Promising
training and testing results are presented in both AirSim simulations and real
flights with DJI F330 Quadrotor equipped with Intel RealSense D435. The
proposed system in action can be found in https://youtu.be/pYvKhc8wrTM.
