A Method for Underwater Human-Robot Interaction Based on Gestures Tracking with Fuzzy Control

Working in collaboration with an Autonomous Underwater Vehicle is a new working method for divers. Using gestures to give instructions for the diver is a simple and effective mode of underwater human-robot interaction (HRI). In this paper, a gestures tracking method for under human-robot interaction based on fuzzy control is proposed. Firstly, four object recognition algorithms in terms of gesture recognition are compared. YOLO V4-tiny was an extremely high performance, as the gesture area recognition algorithm. We propose a model based on Siamese Network for gesture classification. A gesture tracking method based on fuzzy control is proposed, analyzing the image from AUV front camera to establish a 3D fuzzy rule set. This method can realize the self-regulation of AUV and keep the diver's gestures in the camera view. The experiment result shows the efficiency of the proposed method.

Automated summary

This paper introduces a gesture tracking method for underwater human-robot interaction based on fuzzy control. Utilizing YOLO V4-tiny as a gesture area recognition algorithm, a Siamese Network model for gestures classification is proposed, and a 3D fuzzy rule set is established by analyzing images from the AUV front camera. The experiment result demonstrates the efficiency of the proposed method.