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| Kalman tracking algorithm based on realtime vision of pingpong robot |
| ZHANG Yuan-Hui, HUI Wei, YU Dan |
| (College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China) |
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Abstract An adapted measurement covariance digital Kalman filter method was proposed to eliminate the locating noises caused by motion blurring, airdrag and camera image distortion. The method implemented a precise tracking of the target motion trajectory by dynamically changing the measurement covariance, and laid a foundation for target prediction and arm motion. Experimental data showed a good tracking result in condition of camera capturing rate over 70 frame/s and ball motion speed over 5 m/s since the method effectively suppressed interference of noisy measurement and data losing. The method can be employed in cases of fast object tracking for its low computation load and high tracking precision．
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基于实时图像的乒乓机器人Kalman跟踪算法
针对乒乓球高速运动图像模糊、空气阻力以及摄像机成像畸变等因素导致的误差问题,提出一种自适应测量协方差的离散Kalman轨迹估计算法.该算法通过动态调整测量协方差的大小,实现了对目标运动轨迹的准确跟踪,并进一步为乒乓球落点预测和手臂击打奠定了基础.实验表明,在图像采集速率高于70 帧/s、乒乓球速度超过5 m/s的情况下,该算法能有效地克服测量噪声和数据丢失的干扰情况的影响,给出优良的跟踪结果.同时该算法跟踪精度高,计算量小,适用于高速目标跟踪的场合.
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