A depth camera based lightweight visual SLAM algorithm

The Visual SLAM algorithm has the goal of estimating the camera trajectory while reconstructing the Environment, which provides great help for autonomous navigation of mobile robot. However, many SLAM systems improve the complexity of the algorithm in order to show high precision, resulting in poor real-time performance. In practical application, considering the problem of robot life-time and the speed of embedded system, SLAM algorithm needs to improve the real-time performance of the algorithm and ensure the accuracy of application requirements at the same time. This paper presents a lightweight SLAM algorithm, which mainly through the management of map points, multi-threaded design and NEON technology to improve the real-tine performance of the algorithm while still maintaining a good localizing accuracy. It has great reference value for the practical application of SLAM algorithm.