Robot visual SLAM algorithm based on multi-feature information localization

doi:10.13474/j.cnki.11-2246.2025.0403

Abstract

Abstract: The visual simultaneous localization and mapping (SLAM) algorithm has been widely applied in indoor service robots. However, current point cloud, plane-based, and semantic visual SLAM algorithms face issues such as single map structures and inaccurate localization. This paper proposes a multi-layered map construction SLAM (MFIL-SLAM)algorithm based on the classical ORB-SLAM2, incorporating plane and semantic information. The algorithm extracts feature points, planes, and semantic objects from visual and depth images, associates them with map landmarks, updates camera poses, and optimizes multi-layered maps through factor graph optimization. Experimental results demonstrate that the proposed algorithm outperforms existing ones in mapping quality, localization accuracy, and robustness.

Key words: multi-feature information, visual SLAM, data association, factor graph optimization

CLC Number:

P228

FAN Qiliang, DING Dukun. Robot visual SLAM algorithm based on multi-feature information localization[J]. Bulletin of Surveying and Mapping, 2025, 0(4): 14-19,26.

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