Implementation of Robot NAO on Sprint

Implementation of Robot NAO on Sprint

For the widely used humanoid robot Nao, how to apply to the international humanoid robot Olympic competition, and in order to improve the sprint speed of the robot Nao, this paper uses the image processing algorithm to optimize the visual images collected by Nao. The image is filtered and the edge extraction algorithm is used to process the white run line image. Then, the walking control strategy is proposed to calculate the slope of the track centerline and control the motion state of the robot according to the slope value. The experimental results show that the proposed method is feasible and effective in different external environments. In the course of the competition, the interference of the site factors to the Nao path planning is reduced, which improves the speed of the robot and satisfies the robustness of the recognition algorithm in the game.