Fuzzy Controlled Adaptive Follow the Gap Obstacle Avoidance Algorithm

Bilal Yucel, Abdurrahman Yilmaz, Osman Ervan, H. Temeltas
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Abstract

Follow the Gap Method (FGM) and Improved Follow the Gap Method (FGM-I) are geometric obstacle avoidance algorithms for navigation. In these methods, the vehicle detects the gaps around the object and navigates to the midpoint of the optimal gap calculated according to a defined function. One missing point of these algorithms is failure to the goal point when there is an obstacle near to it. Another drawback is that early consideration of obstacles causes long trajectories. In this paper, Adaptive Follow the Gap (A-FGM) is presented to overcome these two points. In A-FGM, a fuzzy controlled evaluation radius is set and only obstacles within this region are included in the evaluation. A differential drive robot is used in simulations and results show that A-FGM increases the success rate of reaching the goal and efficiency of previous algorithms. The source code of the developed approach is shared on GitHub 1.
模糊控制自适应跟随间隙避障算法
遵循间隙法(FGM)和改进遵循间隙法(FGM- i)是用于导航的几何避障算法。在这些方法中,车辆检测物体周围的间隙,并根据定义的函数计算出最佳间隙的中点。这些算法的一个缺失点是当目标点附近有障碍物时无法到达目标点。另一个缺点是早期考虑障碍会导致较长的轨迹。为了克服这两个问题,本文提出了一种自适应间隙跟踪算法(A-FGM)。在a - fgm中,设置一个模糊控制的评价半径,只将该区域内的障碍物纳入评价范围。采用差动驱动机器人进行仿真,结果表明,A- fgm提高了先前算法达到目标的成功率和效率。开发方法的源代码在GitHub 1上共享。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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