  We introduce an early-phase bottleneck analysis and characterization model
called the F-1 for designing computing systems that target autonomous Unmanned
Aerial Vehicles (UAVs). The model provides insights by exploiting the
fundamental relationships between various components in the autonomous UAV,
such as sensor, compute, and body dynamics. To guarantee safe operation while
maximizing the performance (e.g., velocity) of the UAV, the compute, sensor,
and other mechanical properties must be carefully selected or designed. The F-1
model provides visual insights that can aid a system architect in understanding
the optimal compute design or selection for autonomous UAVs. The model is
experimentally validated using real UAVs, and the error is between 5.1\% to
9.5\% compared to real-world flight tests. An interactive web-based tool for
the F-1 model called Skyline is available for free of cost use at:
~\url{https://bit.ly/skyline-tool}
