Waterberry Farms：情報経路計画のための新しいベンチマーク
Waterberry Farms: A Novel Benchmark For Informative Path Planning
精密農業を模した新しいベンチマークWaterberry Farmsを提案し、複数の経路計画・推定アルゴリズムを評価してその有効性を示した。
著者: Samuel Matloob, Partha P. Datta, O. Patrick Kreidl, Ayan Dutta, Swapnoneel Roy, Ladislau Bölöni
分類: cs.RO
原文アブストラクト
Recent developments in robotic and sensor hardware make data collection with mobile robots (ground or aerial) feasible and affordable to a wide population of users. The newly emergent applications, such as precision agriculture, weather damage assessment, or personal home security often do not satisfy the simplifying assumptions made by previous research: the explored areas have complex shapes and obstacles, multiple phenomena need to be sensed and estimated simultaneously and the measured quantities might change during observations. The future progress of path planning and estimation algorithms requires a new generation of benchmarks that provide representative environments and scoring methods that capture the demands of these applications. This paper describes the Waterberry Farms benchmark (WBF) that models a precision agriculture application at a Florida farm growing multiple crop types. The benchmark captures the dynamic nature of the spread of plant diseases and variations of soil humidity while the scoring system measures the performance of a given combination of a movement policy and an information model estimator. By benchmarking several examples of representative path planning and estimator algorithms, we demonstrate WBF's ability to provide insight into their properties and quantify future progress.
