SUMMARYIn this article, hybridization of IWD (intelligent water drop) and GA (genetic algorithm) technique is developed and executed in order to obtain global optimal path by replacing local optimal points. Sensors of mobile robots are used for mapping and detecting the environment and obstacles present. The developed technique is tested in MATLAB simulation platform, and experimental analysis is performed in real-time environments to observe the effectiveness of IWD-GA technique. Furthermore, statistical analysis of obtained results is also performed for testing their linearity and normality. A significant improvement of about 13.14% in terms of path length is reported when the proposed technique is tested against other existing techniques.

中文翻译：

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混合 IWD-GA：模糊静态和动态环境下多移动机器人路径优化和控制方法

总结在本文中，开发并执行了IWD（智能水滴）和GA（遗传算法）技术的杂交，以通过替换局部最优点来获得全局最优路径。移动机器人的传感器用于映射和检测存在的环境和障碍物。所开发的技术在MATLAB仿真平台上进行了测试，并在实时环境中进行了实验分析，以观察IWD-GA技术的有效性。此外，还对获得的结果进行统计分析，以测试它们的线性和正态性。当针对其他现有技术对所提出的技术进行测试时，据报道在路径长度方面有大约 13.14% 的显着改进。