Application Status and Development Trends of Visual SLAM Technology based on Computer Vision

In the field of future technology, artificial intelligence technologies such as autonomous driving, unmanned mobile carrier platforms, and service robots will become the next hotspots, among which simultaneous localization and mapping (SLAM) technology is one of the key technologies. Visual SLAM technology has emerged as a research focus due to its advantages of low economic cost, rich information content, and excellent mapping performance. This paper first introduces the application background, research platforms, and underlying mathematical theories of visual SLAM technology, including computer image processing technology, multi-view geometry, Lie groups and Lie algebras in algebra, and state estimation in probability theory. Subsequently, it elaborates on the specific process of visual SLAM technology for processing video and image data, covering four main components: front-end visual odometry, back-end optimization, loop closure detection, and map construction. Finally, the current application status and technical obstacles of visual SLAM technology are summarized, and prospects for its future optimization and development directions are presented.