A navigation method for underwater unmanned submarine vehicle

By employing a navigation method that combines multi-sensor data fusion and deep reinforcement learning, the problems of navigation accuracy and autonomy of unmanned underwater vehicles in complex environments have been solved, achieving efficient and reliable navigation decisions and promoting the intelligentization of underwater operations.

CN120558233BActive Publication Date: 2026-08-11SHANGHAI JIAOTONG UNIV +1
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Patent Information

Application Number
CN202510874032.2
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2025-06-27
Publication Date
2026-08-11
Estimated Expiration
2045-06-27

AI Technical Summary

Technical Problem

Traditional underwater unmanned vehicle navigation technology suffers from low navigation accuracy, insufficient autonomy and adaptability in complex underwater environments. In particular, it faces problems such as inertial navigation error accumulation, satellite signal attenuation, high cost of underwater acoustic positioning, and high computational resource requirements for visual navigation, making it difficult to meet the needs of modern underwater operations.

Method used

By fusing data from multiple sensors, the system acquires motion state, topography, and aquatic environment data through a high-precision inertial measurement unit, multibeam sonar, underwater camera, and temperature, salinity, and depth sensor. It then combines an improved A* algorithm and a fast exploration random tree algorithm for path planning and utilizes deep reinforcement learning to adjust the navigation strategy, thereby constructing a multi-dimensional environmental state assessment system to optimize navigation decisions.

Benefits of technology

It improves the accuracy and comprehensiveness of underwater environmental perception, optimizes the efficiency and reliability of path planning, enhances the adaptive capability of navigation decision-making, promotes the intelligent development of underwater operations, reduces operating costs, and improves safety.

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Abstract

This invention relates to a navigation method for underwater unmanned vehicles (UUVs), comprising the following steps: acquiring data from multiple sensors and performing spatiotemporal synchronization, feature extraction, and data fusion preprocessing; defining the underwater operating area as a directed graph, with edge weights determined based on terrain complexity, obstacle risk, and water flow influence; based on the directed graph, employing an improved A* algorithm for global path planning and a fast exploratory random tree algorithm for local path planning and dynamic obstacle avoidance; assessing the environmental state considering aquatic environmental parameters, water flow characteristics, and topographic changes; and adjusting the navigation strategy using a deep reinforcement learning algorithm, with the navigation strategy adjustment objective function as the optimization goal, based on the environmental assessment results and the UUV's own state. Compared with existing technologies, this invention offers advantages such as improved navigation accuracy, reliability, and adaptability of underwater UUVs in complex underwater environments.
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