  Recently, there have been numerous advances in the development of
biologically inspired lightweight Micro Aerial Vehicles (MAVs). While
autonomous navigation is fairly straight-forward for large UAVs as expensive
sensors and monitoring devices can be employed, robust methods for obstacle
avoidance remains a challenging task for MAVs which operate at low altitude in
cluttered unstructured environments. Due to payload and power constraints, it
is necessary for such systems to have autonomous navigation and flight
capabilities using mostly passive sensors such as cameras. In this paper, we
describe a robust system that enables autonomous navigation of small agile
quad-rotors at low altitude through natural forest environments. We present a
direct depth estimation approach that is capable of producing accurate,
semi-dense depth-maps in real time. Furthermore, a novel wind-resistant control
scheme is presented that enables stable way-point tracking even in the presence
of strong winds. We demonstrate the performance of our system through extensive
experiments on real images and field tests in a cluttered outdoor environment.
