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An improved constrained differential evolution algorithm for unmanned aerial vehicle global route planning

机译:一种改进的约束差分进化算法,用于无人机全球航路规划

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This paper formulates the global route planning problem for the unmanned aerial vehicles (UAVs) as a constrained optimization problem in the three-dimensional environment and proposes an improved constrained differential evolution (DE) algorithm to generate an optimal feasible route. The flight route is designed to have a short length and a low flight altitude. The multiple constraints based on the realistic scenarios are taken into account, including maximum turning angle, maximum climbing/gliding slope, terrain, forbidden flying areas, map and threat area constraints. The proposed DE-based route planning algorithm combines the standard DE with the level comparison method and an improved strategy is proposed to control the satisfactory level. To show the high performance of the proposed method, we compare the proposed algorithm with six existing constrained optimization algorithms and five penalty function based methods. Numerical experiments in two test cases are carried out. Our proposed algorithm demonstrates a good performance in terms of the solution quality, robustness, and the constraint-handling ability. (C) 2014 Elsevier B.V. All rights reserved.
机译:本文将无人机的全局路径规划问题表述为三维环境中的约束优化问题,并提出了一种改进的约束差分进化算法来生成最优可行路径。该飞行路线被设计为具有较短的长度和较低的飞行高度。考虑了基于实际情况的多重约束,包括最大转弯角,最大爬升/滑坡,地形,禁止飞行区域,地图和威胁区域约束。提出的基于DE的路由规划算法将标准DE与级别比较方法相结合,并提出了一种改进的策略来控制满意的级别。为了显示所提出方法的高性能,我们将所提出的算法与六种现有的约束优化算法和五种基于惩罚函数的方法进行了比较。在两个测试案例中进行了数值实验。我们提出的算法在解决方案质量,鲁棒性和约束处理能力方面表现出良好的性能。 (C)2014 Elsevier B.V.保留所有权利。

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