Visual Control System of a Spraying Robot for Hyphantria cunea Larva Nets

Abstract

In order to implement automatic spraying on Hyphantria cunea larva nets, a spraying robot system with monocular hand-eye coordination and smart targeting abilities was designed according to the target net features. The system realized spatial two-dimensional motions driven by step motors on linear guide rails. Images were processed in real-time to extract the net curtain targets defined using the border area, and the optimal spraying position was then determined. An identification algorithm based on the global net image to distinguish targets before and after spray was proposed. A simulation environment was designed to verify the correctness of this method. Results showed that the highest rate of over spray is 288.5%, and the spray miss rate is 0.