LIBRE: 複数3D LiDARデータセット
LIBRE: The Multiple 3D LiDAR Dataset
10種類のLiDARセンサーから静的ターゲット・悪天候・動的交通の3環境でデータを収集したベンチマーク用データセットを構築し、LiDARの公平な比較と知覚アルゴリズムの改善を可能にした。
著者: Alexander Carballo, Jacob Lambert, Abraham Monrroy-Cano, David Robert Wong, Patiphon Narksri, Yuki Kitsukawa, Eijiro Takeuchi, Shinpei Kato, Kazuya Takeda
分類: cs.RO, cs.CV
原文アブストラクト
In this work, we present LIBRE: LiDAR Benchmarking and Reference, a first-of-its-kind dataset featuring 10 different LiDAR sensors, covering a range of manufacturers, models, and laser configurations. Data captured independently from each sensor includes three different environments and configurations: static targets, where objects were placed at known distances and measured from a fixed position within a controlled environment; adverse weather, where static obstacles were measured from a moving vehicle, captured in a weather chamber where LiDARs were exposed to different conditions (fog, rain, strong light); and finally, dynamic traffic, where dynamic objects were captured from a vehicle driven on public urban roads, multiple times at different times of the day, and including supporting sensors such as cameras, infrared imaging, and odometry devices. LIBRE will contribute to the research community to (1) provide a means for a fair comparison of currently available LiDARs, and (2) facilitate the improvement of existing self-driving vehicles and robotics-related software, in terms of development and tuning of LiDAR-based perception algorithms.
