系统工程与电子技术

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偏微分高程图环境蚁群算法的三维路径规划

肖秦琨, 王弋, 罗艺闯   

  1. 西安工业大学电子信息工程学院, 陕西 西安 710021
  • 出版日期:2015-06-20 发布日期:2010-01-03

3D path planning of ant colony algorithm using partial differential elevation modeling

XIAO Qin-kun, Wang Yi, LUO Yi-chuang   

  1. Department of Electronics and Information Engineering, Xi’an Technological University, Xi’an 710021, China
  • Online:2015-06-20 Published:2010-01-03

摘要:

针对在三维空间路径规划中建模与避障问题,提出了一种新的在偏微分高程建模环境下蚁群算法的三维路径规划方法。首先,利用抽象建模和高程建模方法分别构建三维空间环境,并用偏微分对高程环境进行最优数据提取,在此基础上利用高程数学建模方法进行三维空间重建,最终形成偏微分高程环境。其次,首次将种群对于环境的最佳适应度值作为目标函数评判蚁群寻找最优路径的决策能力。最后,在不同的建模环境中应用蚁群算法进行路径寻优,输出最优路径。通过对仿真结果和实验数据分析,验证了所提方法的有效性和正确性。

Abstract:

A novel three-dimensional (3D) path planning method of the ant colony algorithm under the partial differential elevation modeling is proposed to tackle the problem of scene modeling and obstacle avoidance. Firstly, the 3D abstract scene and elevation scene are built by their modeling respectively, and then the optimal data is extracted from the elevation scene to construct partial differential scene by using the partial differential mathematical method. Furthermore, the best fitness value of the ant colony firstly treated as objective function is employed to display the decision-making capacity of the ant colony in the 3D path planning. Finally, the ant colony algorithm is combined with abstract scene, elevation scene or the partial differential elevation scene, and the best path planning is shown out in 3D scene. Experimental results and statistics analysis show the effectiveness and validity of the proposed algorithm.