Three-dimensional multi-constraint route planning of unmanned aerial vehicle low-altitude penetration based on coevolutionary multi-agent genetic algorithm

来源期刊:中南大学学报(英文版)2011年第5期

论文作者:彭志红 吴金平 陈杰

文章页码:1502 - 1508

Key words:unmanned aerial vehicle (UAV), low-altitude penetration, three-dimensional (3D) route planning, coevolutionary multi- agent genetic algorithm (CE-MAGA)

Abstract:

To address the issue of premature convergence and slow convergence rate in three-dimensional (3D) route planning of unmanned aerial vehicle (UAV) low-altitude penetration, a novel route planning method was proposed. First and foremost, a coevolutionary multi-agent genetic algorithm (CE-MAGA) was formed by introducing coevolutionary mechanism to multi-agent genetic algorithm (MAGA), an efficient global optimization algorithm. A dynamic route representation form was also adopted to improve the flight route accuracy. Moreover, an efficient constraint handling method was used to simplify the treatment of multi-constraint and reduce the time-cost of planning computation. Simulation and corresponding analysis show that the planning results of CE-MAGA have better performance on terrain following, terrain avoidance, threat avoidance (TF/TA2) and lower route costs than other existing algorithms. In addition, feasible flight routes can be acquired within 2 s, and the convergence rate of the whole evolutionary process is very fast.

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