未観測部屋のレイアウト予測による屋内環境探索
Exploration of Indoor Environments Predicting the Layout of Partially Observed Rooms
部分的な地図から未観測の部屋の形状を予測し、その予測を利用して次に移動すべき場所の選択と探索の早期終了を行うことで、屋内環境の探索を効率化する手法を提案した。
著者: Matteo Luperto, Luca Fochetta, Francesco Amigoni
分類: cs.RO, cs.CV
原文アブストラクト
We consider exploration tasks in which an autonomous mobile robot incrementally builds maps of initially unknown indoor environments. In such tasks, the robot makes a sequence of decisions on where to move next that, usually, are based on knowledge about the observed parts of the environment. In this paper, we present an approach that exploits a prediction of the geometric structure of the unknown parts of an environment to improve exploration performance. In particular, we leverage an existing method that reconstructs the layout of an environment starting from a partial grid map and that predicts the shape of partially observed rooms on the basis of geometric features representing the regularities of the indoor environment. Then, we originally employ the predicted layout to estimate the amount of new area the robot would observe from candidate locations in order to inform the selection of the next best location and to early stop the exploration when no further relevant area is expected to be discovered. Experimental activities show that our approach is able to effectively predict the layout of partially observed rooms and to use such knowledge to speed up the exploration.
