Abstract
Vision-based SLAM has an outstanding problem is not work when the camera fast motion, or camera operating environment characterized by scarce. Aiming at this problem, this paper proposes a SLAM method of IMU and vision fusion. This article uses a stereo camera to extract the image ORB feature points. During the camera movement, if the number of extracted feature points is less than a certain threshold and the camera movement cannot be estimated or the estimated camera rotation and translation is greater than a certain threshold, the camera pose is estimated by fusing IMU, Otherwise use feature points to estimate camera pose. This paper uses non-linear optimization methods to perform pose estimation of pure feature points and pose estimation of fused IMU, respectively. The experimental results show that binocular vision SLAM with IMU information can estimate the camera pose more accurately.