都市自動運転のためのマルチLiDARローカリゼーション・マッピングパイプライン
Multi-LiDAR Localization and Mapping Pipeline for Urban Autonomous Driving
4台のLiDARを用いたセンサフュージョンにより、KISS-ICPをベースにしたオフラインマッピングとオンライン自己位置推定を実現し、Autowareに統合したパイプラインを提案した論文。
著者: Florian Sauerbeck, Dominik Kulmer, Markus Pielmeier, Maximilian Leitenstern, Christoph Weiß, Johannes Betz
分類: cs.RO, cs.CV, eess.SP
原文アブストラクト
Autonomous vehicles require accurate and robust localization and mapping algorithms to navigate safely and reliably in urban environments. We present a novel sensor fusion-based pipeline for offline mapping and online localization based on LiDAR sensors. The proposed approach leverages four LiDAR sensors. Mapping and localization algorithms are based on the KISS-ICP, enabling real-time performance and high accuracy. We introduce an approach to generate semantic maps for driving tasks such as path planning. The presented pipeline is integrated into the ROS 2 based Autoware software stack, providing a robust and flexible environment for autonomous driving applications. We show that our pipeline outperforms state-of-the-art approaches for a given research vehicle and real-world autonomous driving application.
関連論文
- uPLAM: 知覚の不確かさを活用したロバストなパノプティック自己位置推定とマッピング自己位置推定・マッピング
