基于动态步长的自适应RRT无人机航路规划

Na Lin, Ya-lun Zhang
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引用次数: 5

摘要

在复杂环境下执行任务时,传统的RRT算法容易使树陷入局部最小区域,导致效率低下。为了解决这一问题,本文提出了一种基于动态步长的自适应RRT算法进行路径规划,并利用三次多项式b样条曲线拟合对规划的路径进行平滑处理。仿真结果表明,与传统RRT算法相比,基于动态步长的自适应RRT算法在第3000次迭代时勘探失败次数减少35186次,消耗时间减少963 ms,距离减少33 km。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An adaptive RRT based on dynamic step for UAVs route planning
Executing task in the complex environment, the traditional RRT algorithm is easy to make the tree fall into local minimum area which resulted in poor efficiency. In order to solve the problem, this paper proposes an adaptive RRT algorithm based on dynamic step for path planning and uses the cubic polynomial BSpline curve fitting to smooth the plannned path. The simulation results show that the number of explore failures reduced 35186 times, consuming time reduced 963 ms, distance reduced 33 km at the 3000th iteration by using the adaptive RRT based on dynamic step comparing to the traditional RRT algorithm.
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