Research on Two Global Path Planning Methods for Autonomous Underwater Vehicle Based on Large-scale Chart Data
Fuguang Ding · Shipbuilding of China · 2004
Global path planning problem for autonomous underwater vehicle (AUV) based on large-scale chart data is investigated by using two methods, which are Genetic Algorithm (GA) and A~* algorithm. This paper introduces environment model based on grid and data structure, in which the nodes of the grid store the digital elevation property. Some problems of GA, such as the coding of chromosome, generating initial population based on knowledge and evaluation function, and the design methods for five generic operators based on domain knowledge etc., are all discussed. And this paper also proposes the realization method for A~* algorithm. The simulation results show that GA makes the path described simply and clearly because of adopting a method of variable length codes, has the character of high speed global convergence, and can more efficiently solve the problem of path planning for AUV; the A~* algorithm can find a relative optimal path to grid in a little time; and both GA and A~* can satisfy the real time requirement for system.