Review of vision-based Simultaneous Localization and Mapping

Abstract

Vision-based simultaneous localization and mapping (VSLAM) which uses visual sensor to make a robot locate itself in an unknown environment while simultaneously construct a map of the environment. With the continuous development of computer vision and robotics, VSLAM has become a supporting technology for popular fields such as unmanned aerial vehicle, virtual reality and unmanned driving. In this paper, the classical framework of visual SLAM is introduced briefly. On this basis, the key technologies and latest research progress of VSLAM from indirect and direct methods are surveyed. Then the research progress of deep learning techniques applied to VSLAM is reviewed. Finally, the development tendency of VSLAM is discussed.