برنامه ریزی مسیر ربات‌متحرک‌ با‌روش‌شطرنجی با‌الگوریتم بهینه سازی گرگ‌خاکستری در‌محیط های ایستا و‌پویا

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی کارشناسی‌ارشد، دانشکده مهندسی برق و کامپیوتر، دانشگاه صنعتی قم، قم، ایران، رایانامه: ali.hatami72@yahoo.com

2 استادیار، دانشکده مهندسی برق و کامپیوتر، دانشگاه صنعتی قم، قم، ایران، رایانامه: sharifi@qut.ac.ir

3 استادیار، دانشکده مهندسی برق و کامپیوتر، دانشگاه صنعتی قم، قم، ایران، رایانامه: yadegar@qut.ac.ir

چکیده

روش گرگ خاکستری، به عنوان یک الگوریتم بهینه‌سازی محاسباتی، اخیراً در حل مسائل بهینه‌سازی و مسائل مسیریابی، الهام گرفته از رفتار گروهی گرگ‌ها، استفاده مؤثری داشته است. این مقاله یک روش فراابتکاری به نام بهینه‌سازی گرگ خاکستری (GWO) با الهام از گرگ‌های خاکستری پیشنهاد می‌کند. چهار نوع گرگ خاکستری مانند آلفا، بتا، دلتا و امگا برای شبیه‌سازی سلسله مراتب رهبری به کار گرفته می‌شوند. به طور کلی، این مقاله بررسی می‌کند که چگونه می‌توان با استفاده از ترکیب دو روش شطرنجی و الگوریتم بهینه‌سازی گرگ خاکستری، مسیر حرکت یک ربات متحرک را در محیط ایستا و نیز محیط پویا بهینه‌سازی کرد. هدف این پژوهش، کوتاه کردن مسیر، کمینه کردن موقعیت نهایی تا هدف، جلوگیری از برخورد و نیز عدم قرارگیری در حداقل‌های محلی است. در این مقاله، الگوریتم بهینه‌سازی گرگ خاکستری به عنوان یک روش مؤثر برای حل مسئله مسیریابی مورد بررسی قرار می‌گیرد. نتایج شبیه‌سازی نشان می‌دهند که استفاده از این الگوریتم، منجر به بهبود قابل توجه در کارایی ربات و بهبود عملکرد مسیریابی در مقابل محیط‌های پیچیده و پویای می‌شود.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Path Planning For A Mobile Robot Using The Chessboard Method And Gray Wolf Optimization Algorithm In Static And Dynamic Environments

نویسندگان [English]

  • Ali Hatami Zadeh 1
  • Javad Sharifi 2
  • Meysam Yadegar 3
1 Msc Student of Qom University of Technology, Faculty of Electrical and computer engineering. Email: ali.hatami72@yahoo.com
2 Assistant Professor of Qom University of Technology, Faculty of Electrical and computer engineering. Email: sharifi@qut.ac.ir
3 Assistant Professor of Qom University of Technology, Faculty of Electrical and Computer Engineering. Email: yadegar@qut.ac.ir
چکیده [English]

The Grey Wolf Optimization (GWO) algorithm, a computational optimization method inspired by the social behavior of wolves, has recently been effectively used to solve optimization and routing problems. This paper proposes a metaheuristic approach named Grey Wolf Optimization (GWO) inspired by grey wolves. Four types of grey wolves, namely alpha, beta, delta, and omega, are employed to simulate the leadership hierarchy. Additionally, three main stages of hunting—searching for prey, encircling prey, and attacking prey—are implemented. Overall, this paper examines how the combination of the chessboard method and the Grey Wolf Optimization algorithm can optimize the path planning of a mobile robot in both static and dynamic environments. The objective of this research is to shorten the path, minimize the final position to the target, avoid collisions, and prevent local minima. This paper investigates the Grey Wolf Optimization algorithm as an effective method for solving the routing problem. Simulation results demonstrate that using this algorithm leads to significant improvements in the robot's efficiency and enhanced path-planning performance in complex and dynamic environments

کلیدواژه‌ها [English]

  • Path Planning
  • Dynamic Environment
  • Grey Wolf Optimization Algorithm
  • Mobile Robot

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