Intelligent Path Planning System for Shallow Submerged Unmanned Ship Based on MS-FA Method

Multi-Sensorfusion (MS) has the characteristics of acquiring accurate and real-time information. Firefly Algorithm (FA) has strong local search capabilities, and it has certain advantages to find the optimal path, but its solution speed is slow. Therefore, on the basis of optimizing the Firefly algorithm, this paper proposes a shallow submersible unmanned ship intelligent path planning system based on the combination of multi-sensor information fusion (MS) and Firefly optimization algorithm (FA). This system solves the problem of traditional unmanned ship path planning, and can achieve the expected effect of shallow submersible unmanned ship avoiding underwater obstacles and shortening the path planning time and distance. Use the machine vision and sonar sensors on the unmanned ship to obtain real-time data for information fusion, and establish a real-time model of the environment. In addition, the FA algorithm is optimized to increase the calculation speed. After that, the real-time model based on MS is combined with the FA optimization algorithm to form a shallow submersible unmanned ship intelligent path planning system. Finally, using Matlab as a simulation tool, based on the establishment of a real-time water environment model, the method proposed is verified through simulation analysis.