Abstract
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.
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Acknowledgements
This work was supported by the National Natural Science Foundation of China under Grant 51679105, Grant 51809112, and Grant 51939003. And this work is partly supported by the Science-Technology Development Plan Project of Jilin Province of China grants 20170101081JC, 20190303006SF, and 20190302107GX.
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Jiang, Y., Zhao, M., Wang, C. et al. A Method for Underwater Human–Robot Interaction Based on Gestures Tracking with Fuzzy Control. Int. J. Fuzzy Syst. 23, 2170–2181 (2021). https://doi.org/10.1007/s40815-021-01086-x
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DOI: https://doi.org/10.1007/s40815-021-01086-x