Global Path Planning of AUV Based on GA-SQP Algorithm

In actual navigation of Autonomous Underwater Vehicle (AUV), global path planning and local path planning should work in coordination. However, when applied to large-scale complex underwater environment, most algorithms have the disadvantage of low search efficiency. In this paper, factors such as terrain threats, navigation distance and energy loss are considered to construct the constraints and objective function of AUV global path planning. By combining integrating Genetic Algorithm (GA) and Sequential Quadratic Programming (SQP) algorithm, the GA-SQP algorithm is proposed to realize the global path planning of AUV in complex underwater environment. This method has the strong robustness and global optimality of the GA algorithm, and effectively inherits the advantages of SQP algorithm in convergence speed and computing efficiency. Simulation results demonstrate that the GA-SQP algorithm can plan the shortest path for AUV in complex underwater environment, and meet the requirements of underwater safety constraints and minimum energy loss.