一种融合激光与视觉的轻量级地貌地图构建方法

doi:10.11896/jsjkx.240400051

Abstract

Abstract: The performance of robots in complex environments is closely related to the interaction with the environment,and traditional geometric mapping can not capture the detailed information of the enviroment adequately.To deal with the problems mentioned above,this study proposes a lightweight terrain map building approach combining laser and vision(LTMB-LV).Based on temporal and spatial synchronization,this method extracts semantic terrain information with improved CSPResnet and fuses it with point clouds to generate semantic point clouds involving terrain information,thereby building a terrain map with terrain description.Meanwhile,local subgraph stitching method based on an improved ICP for optimizing point cloud registration is employed for building terrain maps in large-scale scenarios,while a parallel method enhances real-time performance.Experimental results in real environments demonstrate that the proposed approach can efficiently detect many typical terrains and construct lightweight terrain maps with limited onboard computational power.

Key words: Mobile robots, Lightweight semantic map, Terrain map, Parallel mapping

CLC Number:

TP242

LI Yawen, ZHANG Botao, ZHONG Chaoliang, LYU Qiang. Lightweight Terrain Map Building Approach Combining Laser and Vision[J].Computer Science, 2024, 51(11A): 240400051-9.

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