Intelligent learning and adjustment system for tennis training robot

Abstract

Disclosed is an intelligent learning and adjustment system for a tennis training robot, including an image recognition system, an algorithm model, a back-end processing platform, and an optimization model. Preprocessing of incoming ball data is performed, various necessary data, such as speeds and directions of flying tennis balls, spinning and placements, are collected, various data sets are processed by using various machine learning algorithms, effective predictions and decisions are generated to facilitate the prediction of the placement and difficulty level of the incoming ball, so that a capability and level of a sparring athlete can be evaluated, the tennis training robot accordingly makes prediction and recognition, and carries out interactive feedback actions in a timely manner. The entire training process involves continuously updating of weights and bias values to make the predictions increasingly accurate, and the tennis training robot can provide an interactive intelligent training method.