連続時間軌道を活用した効率的なLiDARバンドル調整によるマルチスキャン位置合わせ
Efficient LiDAR Bundle Adjustment for Multi-Scan Alignment Utilizing Continuous-Time Trajectories
連続時間軌道を最小二乗調整に組み込み、対応探索の枝刈りとアウトオブコアバッファで数千点群を効率的に大域整合させる3D LiDARバンドル調整手法を提案。
著者: Louis Wiesmann, Elias Marks, Saurabh Gupta, Tiziano Guadagnino, Jens Behley, Cyrill Stachniss
分類: cs.RO
原文アブストラクト
Constructing precise global maps is a key task in robotics and is required for localization, surveying, monitoring, or constructing digital twins. To build accurate maps, data from mobile 3D LiDAR sensors is often used. Mapping requires correctly aligning the individual point clouds to each other to obtain a globally consistent map. In this paper, we investigate the problem of multi-scan alignment to obtain globally consistent point cloud maps. We propose a 3D LiDAR bundle adjustment approach to solve the global alignment problem and jointly optimize the available data. Utilizing a continuous-time trajectory allows us to consider the ego-motion of the LiDAR scanner while recording a single scan directly in the least squares adjustment. Furthermore, pruning the search space of correspondences and utilizing out-of-core circular buffer enables our approach to align thousands of point clouds efficiently. We successfully align point clouds recorded with a handheld LiDAR, as well as ones mounted on a vehicle, and are able to perform multi-session alignment.
