UAV向けルーフラインモデル：自律飛行ドローンの機上計算特性を解析するボトルネック分析ツール
Roofline Model for UAVs: A Bottleneck Analysis Tool for Onboard Compute Characterization of Autonomous Unmanned Aerial Vehicles
自律UAVのセンサ・計算・機体動力学の関係をモデル化し、最適な計算機設計を視覚的に分析できるF-1モデルを提案。実機検証で誤差5.1〜9.5%を達成し、WebツールSkylineも公開。
著者: Srivatsan Krishnan, Zishen Wan, Kshitij Bhardwaj, Ninad Jadhav, Aleksandra Faust, Vijay Janapa Reddi
分類: cs.RO, cs.AR
原文アブストラクト
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}
