基于模糊增强人工势场的移动汽车路径规划

Xiaojie Tang, Chengfen Jia, Yao Liu
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引用次数: 0

摘要

自动驾驶技术领域的一个重要研究领域是路径规划。人工势场法是一种常用的局部路径规划分析方法,但其传统算法存在局部最优和目标不可达的缺陷。本研究增强了人工势场法的斥力场表达式,并将模糊控制方法与人工势场法相结合。通过设计两个模糊控制器,实时控制移动汽车的行驶偏转角度和行驶速度,克服了传统人工势场法在一些典型位置关系中的缺陷,使移动汽车更安全、平稳地行驶到目的地,并创建高效的路径规划。Matlab仿真结果表明,改进后的算法能够解决一些常见路径规划位置的目标不可达和局部最优问题,并在避障安全性方面具有优势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fuzzy Enhanced Artificial Potential Field-based Mobile Car Path Planning
A significant area of study in the field of autonomous driving technology is path planning. Artificial potential field approach is a popular technique to analyze local path planning, however, its conventional algorithm suffers the flaws of local optimal and unachievable goals. In this study, the artificial potential field method's repulsive force field expression is enhanced, and the fuzzy control method is integrated with the artificial potential field method. Through the design of two fuzzy controllers, the driving deflection angle and driving speed are controlled in real time, which helps the mobile car to overcome the defects of the conventional artificial potential field method in some typical position relationships, travel more safely and smoothly to its destination, and create efficient path planning. The Matlab simulation results demonstrate the improved algorithm's ability to address the issues of an unreachable objective and a local optimum in a few common path planning places, and also shows advantages in obstacle avoidance safety.
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