GNSS拒否環境における高度マップ勾配を用いたキロメートル級UAVナビゲーション：SPRIN-Dチャレンジ優勝システム
Kilometer-Scale GNSS-Denied UAV Navigation via Heightmap Gradients: A Winning System from the SPRIN-D Challenge
GNSSが使えない環境で、LiDARの局所高度マップと事前の地形高度マップを勾配テンプレートマッチングで照合し、パーティクルフィルタでオドメトリと融合することで、CPUのみでリアルタイムにキロメートル級の自律飛行を実現した機体搭載システム。
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著者: Michal Werner, David Čapek, Tomáš Musil, Ondřej Franěk, Tomáš Báča, Martin Saska
分類: cs.RO
原文アブストラクト
Reliable long-range flight of unmanned aerial vehicles (UAVs) in GNSS-denied environments is challenging: integrating odometry leads to drift, loop closures are unavailable in previously unseen areas and embedded platforms provide limited computational power. We present a fully onboard UAV system developed for the SPRIN-D Funke Fully Autonomous Flight Challenge, which required 9 km long-range waypoint navigation below 25 m AGL (Above Ground Level) without GNSS or prior dense mapping. The system integrates perception, mapping, planning, and control with a lightweight drift-correction method that matches LiDAR-derived local heightmaps to a prior geo-data heightmap via gradient-template matching and fuses the evidence with odometry in a clustered particle filter. Deployed during the competition, the system executed kilometer-scale flights across urban, forest, and open-field terrain and reduced drift substantially relative to raw odometry, while running in real time on CPU-only hardware. We describe the system architecture, the localization pipeline, and the competition evaluation, and we report practical insights from field deployment that inform the design of GNSS-denied UAV autonomy.
関連論文
- PI制御に着想を得た慣性事前分布によるGNSS拒否環境下のUAV半直接視覚ナビゲーションGNSS拒否ナビゲーション
