Virtual robots based on digital images and machine learning in green landscape design

Abstract

Virtual robots, as an intelligent technology, can provide efficient and accurate green landscape design solutions. This study explores the application of virtual robots in green landscape design based on digital images and machine learning techniques. The research and design of a green landscape environment mapping model enables virtual robots to accurately describe green areas. By using advanced sensor technology, virtual robots can perceive key nodes in the environment and construct an accurate map of green areas. Panoramic image synthesis technology utilizes image sensors carried by virtual robots to obtain multiple images in the environment, and concatenates them to generate panoramic images. Through panoramic images, virtual robots can obtain a broader field of view, and improve the accuracy and authenticity of green landscape design. By applying image dehazing algorithms, the impact of fog is effectively reduced, and the clarity and authenticity of the image are improved, enabling designers to better observe and evaluate the greening effect. By perceiving the environment, establishing green area maps, using panoramic images, and applying machine learning processing techniques, virtual robots can accurately perceive the situation of green areas and provide high-quality data and visualization effects for green design.