  Unmanned Aerial Vehicles (UAV), commonly known as drones, have many potential
uses in real world applications. Drones require advanced planning and
navigation algorithms to enable them to safely move through and interact with
the world around them. This paper presents an extended potential field
controller (ePFC) which enables an aerial robot, or drone, to safely track a
dynamic target location while simultaneously avoiding any obstacles in its
path. The ePFC outperforms a traditional potential field controller (PFC) with
smoother tracking paths and shorter settling times. The proposed ePFC's
stability is evaluated by Lyapunov approach, and its performance is simulated
in a Matlab environment. Finally, the controller is implemented on an
experimental platform in a laboratory environment which demonstrates the
effectiveness of the controller.
