【摘要】 乒乓球机器人不能进行成功的智能回球的主要原因是对旋转球的轨迹预测不准确。减小轨迹预测误差可采取如下对策:分析旋转乒乓球飞行过程的运动学模型,采用无迹卡尔曼滤波(UKF)思想构建过程方程和观测方程,根据视觉系统观测得到的三维空间位置信息对乒乓球的三维空间位置、线速度及角速度进行在线估计。通过多次Matlab仿真对比实验和实际对比实验表明,UKF算法相对EKF算法在轨迹预测用时上可节省99%,跟踪误差更小。更多还原

【Abstract】 The inaccurate results of ball trajectory prediction lead to ping-pong robot can not play the table tennis intelligently.In order to reduce the trajectory prediction error,the following measures may taken:The proposed method first analyses the kinematics model of the flying rotary ball,and then constructs the motion equation and observation equation of the ball’s flying trajectory based on the Unscented Kalman Filter(UKF).Finally ping-pong ball’s three-dimensional space position,velocity and angular velocity can be estimated,according to the three-dimensional space position information obtained by a visual observation system.The Matlab simulation experiments and real experimentals show that UKF algorithm compared to EKF algorithm in trajectory prediction time can be saved by 99%,and the tracking error is small.更多还原