基于模糊自调节算法的乒乓球机器人回球速度计算

提出了一种新的回球速度计算模型, 达到以期望的落球速度定点回球的目的. 首先, 忽略了运动过程中马格努斯力的影响, 以多项式拟合乒乓球的运动轨迹, 利用LM算法求解得到回球速度的初始值. 然后, 提出了一种新的基于区域分割的经验数据存储与替换模式, 经线性拟合经验数据得到回球速度, 并与初始速度求加权平均值, 作为模糊调节的初始值. 分析了回球速度的各分量对落点误差的影响, 根据预测的落点误差, 利用模糊算法调节回球速度, 将调整后的结果用于控制回球过程中的球拍位姿与击球速度. 实验结果验证了方法的有效性.

The Computation of Desired Ball Velocity after Striking Based on Self-tunning Fuzzy Algorithm for Robotic Table Tennis

A model of computing the desired velocity of returning balls is developed so that the robot could return the incoming ball to a desired point on the table with a specified landing velocity. Firstly, three polynomials of the flying time are used to fit the ball's trajectory while neglecting the effort of the Magnus force; the initial velocity is obtained after the coefficients of the polynomials are estimated using LM algorithm. Then, a new configuration of storing and replacing experimental data is introduced; the result is received by fitting the stored data. The weighted average of the two results is regarded as the original value of the fuzzy correcting algorithm. With the analysis of the influence of the desired velocity on the error between the actual landing point and the desired point, the velocity is tuned using the fuzzy algorithm after the landing point is predicted. The tuned velocity is the eventual result for controlling the striking speed and posture of the paddle in the process of returning the ball. Finally, experiments were well conducted to verify the performance of the proposed method.