Localization method of mobile robot based on binocular vision and inertial navigation

Abstract

To improve the positioning accuracy of mobile robot, a visual SLAM algorithm based on binocular vision and inertial navigation is presented. In the front part of visual SLAM, a semi-direct binocular visual odometer combining direct method with characteristic method is presented to maintain the fast calculation speed and high accuracy of direct method. In the back-end optimization stage, the visual data and IMU data are fused together, and error functions are constructed in a sliding window in a non-linear optimization way to optimize the accuracy of pose calculation. The algorithm proposed in this paper is validated in EuRoc dataset. The results show that the positioning accuracy of the SLAM system OKVIS, ROVIO and VINS-Mono is significantly improved in both Machine Hall and Vicon Room scenarios, while maintaining high operational efficiency, compared with the open source visual inertial navigation fusion SLAM system OKVIS, ROVIO and VINS-Mono.