A Fast Stereovision Measurement Algorithm Based on SIFT Keypoints for Mobile Robot

When a robot moves independently, it needs to localize itself and avoid obstacles. In order to enable the robot to obtain the depths of surrounding objects, a fast stereovision measurement algorithm based on SIFT keypoints is proposed and implemented on an embedded image processing board based on DSP and FPGA. The calculation of the keypoint descriptor is simplified by directly using the pixel values in the block neighborhood of a keypoint, resulting in an improvement in real-time performance. In order to guarantee the accuracy of searching for the matching points, a two-pass searching strategy is employed, that is, to choose a point in the left image and search the candidate point in the right image, then determine the correspondence by searching the matching point in the left image again. Moreover, for improving the precision of the measurement results, a quadratic polynomial is introduced to compensate the measurement results. Measurement results and comparison of different methods demonstrate the effectiveness of the proposed algorithm. In addition, the measurement system is applied to a mobile robot platform, and the experiment results validate that the system can satisfy the demand of robot applications.