Advancements in Visual Gesture Recognition for Underwater Human–Robot Interaction: A Comprehensive Review

Underwater human-robot interaction (U-HRI) demonstrates a significant potential for enhancing collaboration in challenging underwater tasks such as inspection, maintenance and exploration. Such collaboration demands effective communication. Recent advancements in underwater technology have facilitated the development of cutting-edge autonomous underwater vehicles (AUVs) and sensors. Nevertheless, effective communication remains challenging underwater due to electromagnetic wave attenuation and limited wireless options. As a result, researchers have increasingly focused on visual gesture recognition. This focus is driven by advances in visual sensors and more sophisticated computer vision algorithms. This paper reviews recent progress in deploying visual gesture recognition for U-HRI, leveraging mainly deep learning algorithms to improve communication reliability and efficiency. The main objective is to identify the most promising techniques for practical applications, ultimately enhancing the efficiency and reliability of diver-AUV collaboration.