Rapid Development of Vision-Based Control for MAVs through a Virtual Flight Testbed

We seek to develop vision-based autonomy for small-scale aircraft known as Micro Air Vehicles (MAVs). Development of such autonomy presents significant challenges, in no small measure because of the inherent instability of these flight vehicles. Therefore, we propose a virtual flight testbed that seeks to mitigate these challenges by facilitating the rapid development of new vision-based control algorithms that would have been, in its absence, substantially more difficult to transition to successful flight testing. The proposed virtual testbed is a precursor to a more complex Hardware-In-the-Loop (HILS) facility currently being constructed at the University of Florida. These systems allow us to experiment with vision-based algorithms in controlled laboratory settings, thereby minimizing loss-of-vehicle risks associated with actual flight testing. In this paper, we first discuss our testbed system, both virtual and real. Second, we present our vision-based approaches to MAV stabilization, object tracking and autonomous landing. Finally, report experimental flight results for both the virtual testbed as well as for flight tests in the field, and discuss how algorithms developed in the virtual testbed were seamlessly transitioned to real flight testing.