In view of the intelligent demand of underground roadway support and the precise positioning of underground unmanned fully mechanized face, a method of body positioning measurement of bolting robot based on the principle of monocular vision is proposed. In this paper, a vehicle body positioning model based on image data is established. The data is obtained by camera, and the transformation between image coordinates and world coordinates is completed by coordinate system transformation. The monocular vision positioning system of bolting robot is designed, and the simulation experimental model is built to measure the effective positioning distance of monocular vision positioning system in the simulation experimental conditions. The experimental platform of bolting robot is designed, and the vehicle is measured Real time data of body positioning, analysis of experimental error and demonstration of reliability of the method. In this method, the real-time localization of underground mine is realized by the robot of bolting, and the accuracy and efficiency of localization are improved, which lays the foundation for the localization control of mining face and the automation and unmanned of the robot of bolting.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.