Neural network-based recognition of navigation environment for intelligent shipyard welding robots

Abstract

A robotic welding system for closed block assembly in shipyard needs a sensor system for the recognition of the working environments and the weld seam tracking, and a specially designed environment recognition strategy. In the paper, the developed 3D sensor system is briefly introduced, and a strategy of environmental recognition for welding mobile robot navigation is developed in order to recognize work environments efficiently. The task space formed between two lengths within closed blocks is classified into far field. middle field, and near field, according to the robot-to-welding environment distance. The recognition strategy and tactics for sensing the work environment and detecting the obstacles are described and discussed in derail. Finally, a neural network structure for obstacle classification is proposed and tested in a real work environment.