基于模糊推理的机器人路径规划与平滑

Kuo-Ho Su, Tan-Phat Phan
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引用次数: 6

摘要

为了在障碍物空间中引导自主机器人,本文提出了一种基于模糊推理的增强路径规划系统,包括图像处理、聚类约简、路径规划和平滑。为了缩短路径规划时间,首先将捕获图像中的障碍物聚类成较小的组;作为一种路径生成的路线图方法,模糊推理机制被连续使用。为了使规划路径平滑,提出了一种基于第二模糊推理机制的粗糙路径点移动算法。为了验证该系统的有效性,进行了仿真。仿真结果表明,在各种障碍物布局下,自主机器人都具有良好的路径规划和平滑性能,能够安全到达目标。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Robot path planning and smoothing based on fuzzy inference
To guide an autonomous robot in the space of obstacles, an enhanced path planning system including image processing, cluster reduction, path planning and smoothing based on fuzzy inference is proposed in this paper. To shorten the path planning time, the obstacles in the captured image are clustered into smaller groups firstly. Being a roadmap method for path generation, the fuzzy inference mechanism is employed consecutively. To smooth the planned path, a novel algorithm based on second fuzzy inference mechanism is proposed to move the rough waypoints. To verify the effectiveness of the proposed system, some simulations are carried out. From the simulations, the autonomous robot possesses good path planning and smoothing performance to reach its goal safely under various obstacle layouts.
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