交差点識別を用いた意味・トポロジカルマッピング
Semantic and Topological Mapping using Intersection Identification
ロボットのナビゲーション向けに、交差点や行き止まりなどを識別して意味的・トポロジカルな地図を生成する手法を提案し、従来手法より最大89%少ないノード数で地図を構築できることを示した。
著者: Scott Fredriksson, Akshit Saradagi, George Nikolakopoulos
分類: cs.RO
原文アブストラクト
This article presents a novel approach to identifying and classifying intersections for semantic and topological mapping. More specifically, the proposed novel approach has the merit of generating a semantically meaningful map containing intersections, pathways, dead ends, and pathways leading to unexplored frontiers. Furthermore, the resulting semantic map can be used to generate a sparse topological map representation, that can be utilized by robots for global navigation. The proposed solution also introduces a built-in filtering to handle noises in the environment, to remove openings in the map that the robot cannot pass, and to remove small objects to optimize and simplify the overall mapping results. The efficacy of the proposed semantic and topological mapping method is demonstrated over a map of an indoor structured environment that is built from experimental data. The proposed framework, when compared with similar state-of-the-art topological mapping solutions, is able to produce a map with up to 89% fewer nodes than the next best solution.
