Research and Implementation of SLAM System Based on Vision and Laser Fusion in Unknown Environment
Realizing autonomous navigation and environmental mapping of robots in unknown environments is a highly challenging research topic,and SLAM is one of the key technologies to address this challenge.Based on the analysis of research status,system scheme design,technical implementation,and experimental verification,combined with the advantages of vision and laser,a SLAM system based on vision and laser fusion in an unknown environment is designed.By using a balanced selection strategy for keyframes and sliding windows,as well as a classification optimization strategy,the initial pose and feature points are optimized,which improves the robustness of the system and can output high-precision maps;the feasibility and practicality of the proposed algorithm are verified through the implementation of a demonstration system using intelligent cars as carriers.
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