Ball-hitting method and device for table tennis robot

Abstract

The embodiment of the invention discloses a ball-hitting method and device for a table tennis robot. The method comprises the following steps: acquiring track points of a preset number of table tennis balls, forecasting flight tracks of the table tennis balls, and acquiring positions Phit, incident velocities Vin and remaining times t of best hitting points after the table tennis balls enter an operation space of the robot; calculating the reflection velocities VOut of the hit table tennis balls; calculating racket velocities VR and postures WTR according to collision models of the table tennis balls and a racket through the incident velocities Vin and the reflection velocities Vout of the table tennis balls at the positions Phit of the best hitting points; driving the racket at the tail end of the robot to finish a hitting action within the remaining times according to the racket speeds VR and the postures WTR. By adopting the ball-hitting method and device for the table tennis robot, the racket velocities and directions are configured, and the racket velocities and postures are calculated by the collision models of the table tennis balls and the racket, so that accurate drop point control of the tablet tennis balls on a half table of an opponent is realized after table tennis robot hits the table tennis balls.

Description

technical field [0001] The embodiments of the present invention relate to the technical field of control, in particular to a ball hitting method and device for a table tennis robot. Background technique [0002] At this stage, there are mainly two batting methods. The first method is: the batting method based on the collision model between the table tennis ball and the racket, including the mirror reflection model and the nonlinear collision model, and both use model analysis to obtain the attitude and speed of the racket; The second way is to obtain the attitude and speed of the racket through machine learning through a large number of data samples. [0003] The specular reflection model in the first method is relatively simple and easy to implement, but because the collision characteristics between the table tennis ball and the racket are ignored, there is a relatively large deviation between the specular reflection model and the real collision model, so this method is use...

AI Technical Summary

Problems solved by technology

[0005] The purpose of the embodiments of the present invention is to propose a table tennis robot hitting met

Images