Efficient algorithms for navigation of underwater vehicles with communication constraints. An overview

Because of the Autonomous Underwater Vehicles (AUVs) potential for use in marine and oceanographic research, as well as in sectors like environmental monitoring and oil and gas development, underwater exploration and offshore wind energy, research in the underwater environment has gained a lot of attention in recent years. AUV navigation in the complicated and unpredictable underwater environment is one of the biggest challenges. Research in underwater technology has advanced dramatically, and current AUVs with proper path planning can operate for prolonged periods of time at vast depths to complete the underwater operations. This study investigates several paths planning techniques, classifying them as local or global strategies, and incorporates classical, graph-based, and intelligent optimization algorithms to improve navigation and obstacle avoidance. The examination focuses on the history of these approaches, demonstrating their increased efficiency in dynamic and complicated situations. This overview addresses the challenges that AUVs encounter in the maritime environment, notably in terms of course navigation planning and communication constraints. When applying these algorithms to AUV path planning issues, researchers frequently include extra limitations and goals unique to underwater environments, such as currents, obstructions, energy consumption, and communication constraints. It places a strong emphasis on navigating an ideal path between the starting to the end point. The global and local components of the path planning method are used to address for AUVs using efficient navigation algorithms are briefly discussed in this review study based on their advantages and disadvantages. A suggestion for additional research on AUV path planning is made on effectiveness of the reported path planning the strategies will serve as a catalyst to inspire researchers within the field to concentrate on specific issues identified for the future advancement of AUVs. The global and local path planning methods are used to address navigation based on tradition, group intelligent optimization and graph search algorithms.