Inspection and maintenance of industrial infrastructure with autonomous underwater robots

Enhancing Underwater SLAM Navigation and Perception: A Comprehensive Review of Deep Learning Integration

Underwater simultaneous localization and mapping (SLAM) is essential for effectively navigating and mapping underwater environments; however, traditional SLAM systems have limitations due to restricted vision and the constantly changing conditions of the underwater environment. This study thoroughly examined the underwater SLAM technology, particularly emphasizing the incorporation of deep learning methods to improve performance. We analyzed the advancements made in underwater SLAM algorithms. We explored the principles behind SLAM and deep learning techniques, examining how these methods tackle the specific difficulties encountered in underwater environments. The main contributions of this work are a thorough assessment of the research into the use of deep learning in underwater image processing and perception and a comparison study of standard and deep learning-based SLAM systems. This paper emphasizes specific deep learning techniques, including generative adversarial networks (GANs), convolutional neural networks (CNNs), long short-term memory (LSTM) networks, and other advanced methods to enhance feature extraction, data fusion, scene understanding, etc. This study highlights the potential of deep learning in overcoming the constraints of traditional underwater SLAM methods, providing fresh opportunities for exploration and industrial use.

Review of Computational Fluid Dynamics Analysis in Biomimetic Applications for Underwater Vehicles

Biomimetics, which draws inspiration from nature, has emerged as a key approach in the development of underwater vehicles. The integration of this approach with computational fluid dynamics (CFD) has further propelled research in this field. CFD, as an effective tool for dynamic analysis, contributes significantly to understanding and resolving complex fluid dynamic problems in underwater vehicles. Biomimetics seeks to harness innovative inspiration from the biological world. Through the imitation of the structure, behavior, and functions of organisms, biomimetics enables the creation of efficient and unique designs. These designs are aimed at enhancing the speed, reliability, and maneuverability of underwater vehicles, as well as reducing drag and noise. CFD technology, which is capable of precisely predicting and simulating fluid flow behaviors, plays a crucial role in optimizing the structural design of underwater vehicles, thereby significantly enhancing their hydrodynamic and kinematic performances. Combining biomimetics and CFD technology introduces a novel approach to underwater vehicle design and unveils broad prospects for research in natural science and engineering applications. Consequently, this paper aims to review the application of CFD technology in the biomimicry of underwater vehicles, with a primary focus on biomimetic propulsion, biomimetic drag reduction, and biomimetic noise reduction. Additionally, it explores the challenges faced in this field and anticipates future advancements.