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| Online angular velocity estimated visual measurement for ping pong robot |
| ZHANG Yuan-hui1,2,WEI Wei2 |
1. College of Mechanical and Electrical Engineering, China Jiliang University, Hangzhou 310018, China;
2. College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China |
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Abstract Currently, the failure of precisely identifying and tracking the spin ball trajectory in ping pong robot's vision system leads to large errors in the predicting result. Aiming at the problem, an online nonlinear Kalman filter based visual measurement method was proposed to estimate the angular velocity. Aerodynamics theory was applied to analyze the forces acting on the spin ball. The motion equation and observation equation of the trajectory were constructed, and the nonlinear extended Kalman filter was integrated to estimate the motion states involving the angular velocity. Both simulation and actual experiments verified the effectiveness and correctness of the method. The prediction result outperformed other tracking methods. The method can also be employed in the high-speed motion tracking conditions．
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Published: 01 July 2012
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在线角速度估计的乒乓球机器人视觉测量方法
针对目前乒乓球机器人在视觉跟踪过程中无法准确识别和跟踪旋转球轨迹,导致预测结果误差较大的问题,提出基于在线旋转角速度估计的视觉测量方法.该方法应用空气动力学的理论知识对旋转球的受力情况进行分析建模,构建旋转球轨迹的过程方程和观测方程,利用非线性扩展Kalman滤波器对包括角速度在内的运动状态进行估计.通过仿真实验和实际轨迹跟踪实验验证了该方法的有效性和正确性,且预测结果优于同类跟踪方法.该方法亦可应用于实时高速目标跟踪的场合.
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