構造化SLAMのための重み付き等角LiDARマッピング
Weighted Conformal LiDAR-Mapping for Structured SLAM
生のLiDAR計測データから等角メビウス変換を用いて多角形プロファイルを抽出し、不確かさを伝播させることで、構造化環境におけるSLAMの計算効率を大幅に改善する手法を提案した論文。
著者: Natalia Prieto-Fernández, Sergio Fernández-Blanco, Álvaro Fernández-Blanco, José Alberto Benítez-Andrades, Francisco Carro-De-Lorenzo, Carmen Benavides
分類: cs.RO
原文アブストラクト
One of the main challenges in simultaneous localization and mapping (SLAM) is real-time processing. High-computational loads linked to data acquisition and processing complicate this task. This article presents an efficient feature extraction approach for mapping structured environments. The proposed methodology, weighted conformal LiDAR-mapping (WCLM), is based on the extraction of polygonal profiles and propagation of uncertainties from raw measurement data. This is achieved using conformal M bius transformation. The algorithm has been validated experimentally using 2-D data obtained from a low-cost Light Detection and Ranging (LiDAR) range finder. The results obtained suggest that computational efficiency is significantly improved with reference to other state-of-the-art SLAM approaches.