Intelligent Control Method of Live Working Robot Based on Cloud and Edge Computing Terminal

Abstract

The existing single machine working mode of live working robots cannot meet the computational power requirements of artificial intelligence high-precision algorithm, and it is difficult to adapt to the complex working scene, and cannot be applied to the scene where a large number of robots work at the same time to generate massive data management and control. In view of the existing shortcomings, this paper analyzes and compares the working modes of existing power grid inspection robots and live working robots, and proposes an intelligent management and control method for live working robots based on cloud and edge computing terminals. By deploying different parts of deep learning algorithm in cloud and edge computing terminal, the problems existing in the previous working mode are solved. A typical example of live working robot scene in substation is analyzed. The results show that the intelligent control method proposed in this paper can meet the computational power requirements of artificial intelligence deep learning, neural network coordinated control, recognition and control model self-learning, self-renewal and other high-precision algorithm, and can be applied to the scene of complex environment or a large number of robots working at the same time to produce massive data control.