UAVによる能動的分類のためのオンライン情報経路計画
Online Informative Path Planning for Active Classification on UAVs
農地の雑草検出を目的に、占有格子で雑草分布をモデル化し、情報理論的目的関数に基づいてUAVの経路をオンラインで計画する手法を提案。シミュレーションで従来の全面走査と比較検証した。
著者: Marija Popovic, Gregory Hitz, Juan Nieto, Roland Siegwart, Enric Galceran
分類: cs.RO
原文アブストラクト
We propose an informative path planning (IPP) algorithm for active classification using an unmanned aerial vehicle (UAV), focusing on weed detection in precision agriculture. We model the presence of weeds on farmland using an occupancy grid and generate plans according to information-theoretic objectives, enabling the UAV to gather data efficiently. We use a combination of global viewpoint selection and evolutionary optimization to refine the UAV's trajectory in continuous space while satisfying dynamic constraints. We validate our approach in simulation by comparing against standard "lawnmower" coverage, and study the effects of varying objectives and optimization strategies. We plan to evaluate our algorithm on a real platform in the immediate future.
