森林におけるUrquhartテセレーションを用いた場所認識
Place Recognition in Forests with Urquhart Tessellations
森林内の木の位置からUrquhartテセレーションに基づく新規記述子を構築し、部分的な重なりやノイズがあっても過去の観測やランドマーク対応を検出するフレームワークを提案。UAVの実飛行データでループ閉鎖検出と地図統合を行い、精度とロバスト性で既存手法を上回ることを示した。
著者: Guilherme V. Nardari, Avraham Cohen, Steven W. Chen, Xu Liu, Vaibhav Arcot, Roseli A. F. Romero, Vijay Kumar
分類: cs.CV, cs.RO
原文アブストラクト
In this letter, we present a novel descriptor based on Urquhart tessellations derived from the position of trees in a forest. We propose a framework that uses these descriptors to detect previously seen observations and landmark correspondences, even with partial overlap and noise. We run loop closure detection experiments in simulation and real-world data map-merging from different flights of an Unmanned Aerial Vehicle (UAV) in a pine tree forest and show that our method outperforms state-of-the-art approaches in accuracy and robustness.
