11/7/2022 0 Comments Electro air hockey downloadThe first type is to divide the detection problem into two stages. The currently developed target detection algorithms are divided into two types. ĭue to the development of convolutional neural networks, many people began to apply neural networks to image recognition. Compared with directly extracting the puck position for trajectory prediction, some have proposed adding a high-speed vision system to capture the player’s attacking postures and movements to make the basis for the robot’s return decision, or to analyze the eye movements of human players to generate a return strategy using the human eye to determine the lack of time, and some people make a control mechanism based on reinforcement learning to reduce the rate of missing points of this system. Position prediction uses the angle, speed, and position of the puck through the attack line as input data to train a neural network model that can predict the position of the puck through the finish line. It was also proposed to use a neural network for the end point. The prediction first assumes that the puck moves in a straight line, and a linear formula is used as the prediction method after the last impact on the edge of the table or after the puck enters the specified area. The mutual conversion of the color space is used to eliminate the influence of the brightness on the color characteristics of the puck. Related works usually got the position of the puck by traditional image recognition.
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