关键词: 足球机器人, 球速估计, 随机采样一致算法, Kalman滤波

Abstract: A new method was proposed to estimate the ball velocity in the Robot World Cup (RoboCup) Middle Size League (MSL) more effectively. The method was based on Kalman filter and RANSAC algorithm. Firstly several frames of the ball positions were stored and then Kalman filter was used to optimize the positions. Hundreds of models were built and RANSAC algorithm was employed to calculate the best model as the final ball velocity. The experimental results show that the proposed algorithm is effective. Furthermore, RANSAC algorithm can eliminate the outlier effectively, so when there are lots of noises in the ball information, the ball velocity can still be estimated with high accuracy by using the presented algorithm, and higher robustness can be achieved being compared with the other existing methods.

Key words: soccer robot, ball velocity estimation, Random Sample Consensus (RANSAC) algorithm, Kalman filter