建設現場におけるAutoware：オフロード自動運転に向けたギャップ分析とLiDAR知覚
Autoware in Construction: Gap Analysis and LiDAR Perception Toward Off-Road Autonomous Driving
建設現場の大型ダンプトラックにAutowareを適用するため、公道とのギャップを分析し、LiDAR知覚パイプラインの開発と実地試験の知見を報告した。
詳しい要約
1. どんなもの？
2. 先行研究と比べてどこがすごい？
3. 技術・手法の肝は？
4. どうやって有効だと検証した？
5. 議論はある？
6. 次に読むべき論文は？
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著者: Yu Otsuki, Teja Emmey, Sena Matsushita, Akiro Harada, Takeshi Miura
分類: cs.RO
原文アブストラクト
Autoware is an open-source autonomous driving software platform widely adopted by researchers and industry developers. Originally developed primarily for public-road applications, including passenger vehicles, taxis, and buses, Autoware is increasingly being extended to off-road environments such as construction and agricultural sites. Construction sites, however, differ fundamentally from public roads and challenge many assumptions underlying conventional autonomous driving systems. They are characterized by unstructured terrain, airborne dust, continuously evolving site conditions, and construction-specific objects. This paper presents lessons learned from ongoing efforts to extend an Autoware-based autonomous driving system to large dump trucks operating at construction sites. We identify gaps between public-road and off-road construction applications across the sensing, mapping, localization, perception, planning, and control modules of the Autoware stack. We then discuss potential solutions for addressing these gaps, with particular emphasis on ongoing LiDAR-based perception pipeline development and findings from field testing. Finally, we propose a roadmap toward end-to-end autonomous driving for construction vehicles.