Indoor hierarchy relation graph construction method based on RGB‐D

Abstract

Fine‐grained indoor navigation services require obstacle‐level indoor maps to support, but since indoor environments are affected by human activities, resulting in frequent changes in indoor spatial layouts, and indoor environments are easily affected by light and occlusion, the vast majority of indoor maps are at room level, limiting indoor obstacle‐level navigation path planning. To solve this problem, this paper proposes a hierarchy relation graph (HRG) construction method based on RGB‐D. Firstly, the semantic information extraction of indoor scenes and elements is realized by the output transformed PSPNet and YOLO V8 models, and the bounding box of each element is obtained based on YOLO V8. Then an algorithm for determining the hierarchical relationship of indoor elements is proposed, which calculates the correlation between the two elements from both plane and depth dimensions and constructs a HRG of indoor elements based on directed trees. Finally, comparative experiments are designed to validate the proposed method. Experiments showed that the proposed method can construct HRGs in a variety of scenes; the hierarchy relation detection rate is 88.28%; the accuracy of hierarchy relation determination is 73.44%; and the single‐scene HRG can be generated in 3.81 s.