自動運転のための意味的3Dグリッドマップ
Semantic 3D Grid Maps for Autonomous Driving
自動運転向けに、リアルタイム制約を満たしつつ3D表現と意味情報を統合する階層的3DグリッドマッピングフレームワークUFOMapを提案し、遮蔽空間計算やセマンティックセグメンテーションの統合に有効であることを示した。
著者: Ajinkya Khoche, Maciej K Wozniak, Daniel Duberg, Patric Jensfelt
分類: cs.RO
原文アブストラクト
Maps play a key role in rapidly developing area of autonomous driving. We survey the literature for different map representations and find that while the world is three-dimensional, it is common to rely on 2D map representations in order to meet real-time constraints. We believe that high levels of situation awareness require a 3D representation as well as the inclusion of semantic information. We demonstrate that our recently presented hierarchical 3D grid mapping framework UFOMap meets the real-time constraints. Furthermore, we show how it can be used to efficiently support more complex functions such as calculating the occluded parts of space and accumulating the output from a semantic segmentation network.
