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We introduce an early-phase bottleneck analysis and characterization modelcalled the F-1 for designing computing systems that target autonomous UnmannedAerial Vehicles (UAVs). The model provides insights by exploiting thefundamental relationships between various components in the autonomous UAV,such as sensor, compute, and body dynamics. To guarantee safe operation whilemaximizing the performance (e.g., velocity) of the UAV, the compute, sensor,and other mechanical properties must be carefully selected or designed. The F-1model provides visual insights that can aid a system architect in understandingthe optimal compute design or selection for autonomous UAVs. The model isexperimentally validated using real UAVs, and the error is between 5.1\% to9.5\% compared to real-world flight tests. An interactive web-based tool forthe F-1 model called Skyline is available for free of cost use at:~\url{https://bit.ly/skyline-tool}

Roofline Model for UAVs: A Bottleneck Analysis Tool for Onboard Compute Characterization of Autonomous Unmanned Aerial Vehicles