User entertainment experience analysis of artificial intelligence entertainment robots based on convolutional neural networks in park plant landscape design

Abstract

Currently, the application of artificial intelligence entertainment robots in park plant landscape design has attracted increasing attention. This study aims to design an artificial intelligence entertainment robot that can provide a high-quality user experience. Through virtual reality and robotics technology, designers can be provided with visual and entertaining design solutions, and more interactive experiences can be provided for design clients. Convolutional neural networks can effectively extract features from images, and utilizing spectral feature extraction technology to further improve the accuracy of image recognition. Subsequently, this study designed a robot control system and calibrated the hand eye system. The robot control system can coordinate the various functions of the robot and ensure its smooth operation in the park plant landscape design. The calibration of the hand eye system is to ensure that the robot can accurately perceive the environment and locate its own position. Through real-time control strategies, robots can respond and adjust in a timely manner based on current environmental changes and user needs. By comparing with the actual position on the ground, the accuracy of robot positioning is obtained, and the system is further optimized and improved.