Application of Neural Networks in Underwater Drone Control

  • 1 AGH University of Kraków


The integration of neural networks has revolutionised various technological domains, including the control mechanisms of underwater drones, especially in the context of Industry 4.0. This review explores the application of neural network architectures to improve the navigation, stability and overall performance of underwater drones. A systematic analysis of current methods is provided, focusing on their effectiveness in addressing challenges such as dynamic underwater environments, sensor noise, and real-time decision making. Key advances in neural network-based control strategies are discussed. Furthermore, the integration of these networks with traditional control systems to achieve robust and adaptive control frameworks is highlighted. Through the examination of case studies and experimental results, this review identifies potential areas for future research and development to further the advancement of autonomous underwater vehicles through intelligent control systems.



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