Human-Computer Interaction Control of Snake-Like Robot Based on Gesture Recognition

Abstract

Human-computer interaction has been a hot topic in the development of robots. Gesture recognition is a significant part of it. Existing snake-like robot is controlled by the handle and joystick. It is worth studying that use gesture to control robots. Existing main vision-based gesture recognition methods are based on a two-stage method: hand detection and segmentation, feature extraction and template matching process. Inspired by the YOLO[1] algorithm, this paper proposed a one-stage gesture recognition and snake-like robot control method, based on deep learning, combined image segmentation and classification, realized end-to-end recognition and robot control. The snake-like robot can react to four types of human's gestures with a rapid processing time.