Abstract: The robot's self-localization is the key to realize navigation and intelligent. To deal with the accuracy of location problem of the flying robot in indoor environment, an improved visual odometry/SINS integrated localization algorithm based on BA is proposed. First, the proposed method combines the calculation of visual information by direct method with the angular velocity and acceleration information of inertial unit, and iterate using extended Kalman filter method, which enhances the robustness of the visual odometry. The estimation preciseness of feature points' depth information is improved with inverse depth method. Then bundle adjustment is used for local optimization. The experiment results show that the proposed algorithm has effectively improved the preciseness of robot-pose estimation.

Key words: inertial measuring unit (IMU), direct methods, visual odometry, bundle adjustment