A Drone Human-Machine Interaction Method Based on Generative Adversarial Network

Abstract

Commercially drone are mainly operated by dedicated personnel with trained skills. The high learning cost of operation will discourage some potential users. In this paper, we propose an human-machine Interaction to drone by intercepting the visual images of robots and use Generative Adversarial Network(GAN) to train. A camera is used to intercept the operator's gestures, and the photos with the operator's gestures are converted into control commands to improve the accuracy of operation in complex backgrounds. As a result of this research, drone flight control can be accomplished in more complex backgrounds, greatly simplifying operator stress.