Neural Network Design for a Curved Kicking Mechanism with Obstacle Avoidance in RoboCup Small Size League (SSL)

Abstract At the RoboCup, a robotics soccer tournament, the Small Size League (SSL) is one of its leagues. The thought of a mechanism in this league that could perform unpredictable kicks and passes inspired study into both the physical mechanism required to do it and the algorithms needed to make the most of it.By introducing new ideas and utilizing a Deep Neural Network, this work contributes by improving a prior algorithm that aims to carry out a real-time inversion of the non-linear ordinary differential equation (ODE) that models the ball’s path in order to determine the parameters to hit a target with a curved kick mechanism (DNN). New techniques are also presented. The two suggested DNN achieved accuracy levels of more than 92% in the outcomes of simulation runs in MATLAB.