Analysis of feature point matching technology in SLAM based on binocular vision

Abstract

With rapidly developing computing technology, intelligent robots have been used extensively in many areas of life, improving work efficiency and lowering labor costs. At the same time, with the increasing number of robot application scenarios, the demand for robot intelligence has also increased. Computer vision-based simultaneous localization and mapping (SLAM) technology is a key technology that helps robots achieve real-time positioning and navigation in order to improve their intelligence. Feature point matching is an important component of this technology. This paper mainly analyzes the current development status of feature point matching technology in visual SLAM. Firstly, a brief introduction was given to the three widely used SLAMs, and the advantages and disadvantages of different SLAM technologies were analyzed. Second, a brief presentation and explanation of the working principle of binocular SLAM technology were provided. Then, the basic principles and key points of feature point recognition and matching techniques in several different algorithms for visual SLAM were summarized. Analyzed the advantages and disadvantages of various algorithms, as well as improvements based on this algorithm. Finally, summarize and provide suggestions for the future development of visual SLAM technology.