  Unmanned aerial vehicles (UAV) are commonly used for missions in unknown
environments, where an exact mathematical model of the environment may not be
available. This paper provides a framework for using reinforcement learning to
allow the UAV to navigate successfully in such environments. We conducted our
simulation and real implementation to show how the UAVs can successfully learn
to navigate through an unknown environment. Technical aspects regarding to
applying reinforcement learning algorithm to a UAV system and UAV flight
control were also addressed. This will enable continuing research using a UAV
with learning capabilities in more important applications, such as wildfire
monitoring, or search and rescue missions.
