静态二维环境下无人机DFMB算法的计算研究

Subhradip Mukherjee, Rajagopal Kumar, Siddhanta Borah
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引用次数: 0

摘要

本文提出了一种随机顺时针或逆时针运动的距离函数修正错误(DFMB)算法;提供最佳路径长度和更少的运行时间;可用于无人驾驶车辆的路径跟踪。并将该算法的运行时间偏差百分比与其他现有算法进行了比较。在存在障碍的静态2D环境中;传统的Bug方法是首先寻找从起点到目标位置的最短路径,然后沿着这条路径走。如果路径经过任何障碍,那么它就会开始跟随行为,以找到到达目标的最短路径。在我们的方法中,我们引入了一种改进的距离计算方法,其中包含了一些新开发的参数。DFMB算法在给定的二维环境中提供了从源到目标位置的平滑轨迹,并且可以避开障碍物,而不会盲目跟随障碍物的边界。各种仿真结果和适当的对比分析证明了该算法的优越性。我们利用MATLAB对该算法进行了有效的实现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Computational Study of DFMB Algorithm for Unmanned Vehicle in Static 2D Environment
In this paper, a Distance Function Modified Bug (DFMB) Algorithm with a random clockwise or anti-clockwise movement has been presented; offering optimum path length and less run time; which can be used for unmanned vehicle path tracking. Percent deviation in the run time of the algorithm has been compared with the other existing algorithms. In a static 2D environment where an obstacle is present; the traditional Bug approach is to first seek the shortest path from start to goal location and follow that path. If the path passes through any obstacle, then it starts wall following behaviour to find the shortest way to the goal. In our approach, we have introduced an improved distance calculation method with some newly developed parameters. The DFMB algorithm offers a smooth trajectory from source to goal location with obstacle avoidance in a given 2D environment without blindly following the boundary of the obstacle. Various simulation results and suitable comparative analysis have been presented to prove the superiority of the algorithm. We have done the effective realization of the algorithm, using MATLAB.
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