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An algorithm of visual odometer based on average gradient

During the movement, the walking robot will rive the depth camera up and down to vibrate, and the movement speed will sometimes be too fast, making the image blurred. We know that feature matching is the link of VSLAM to establish data association. A large number of mismatches will have a significant impact on the system. Once the image is blurred, the entire system will collapse. The purpose of this paper is to set a threshold H to judge the clarity of the image. We choose the algorithm for extracting the feature points according to the clarity of the image. At the expense of a little time, the system can extract more feature points and reduce mismatches in the case of high ambiguity, so as to be more stable for the subsequent calculation of pose and preserves good initial conditions for subsequent map optimization.