Geodesic
An effective global path planning algorithm with teaching-learning-based optimization
Kybernetika, Tome 60 (2024) no. 3, pp. 293-316 Cet article a éte moissonné depuis la source Czech Digital Mathematics Library

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Due to the widespread use of mobile robots in various applications, the path planning problem has emerged as one of the important research topics. Path planning is defined as finding the shortest path starting from the initial point to the destination in such a way as to get rid of the obstacles it encounters. In this study, we propose a path planning algorithm based on a teaching-learning-based optimization (TLBO) algorithm with Bezier curves in a static environment with obstacles. The proposed algorithm changes the initially randomly selected control points step by step to obtain shorter Bezier curves that do not hit obstacles. We also improve the genetic algorithm-based path planning algorithm. Experimental results show that they provide better paths than other existing algorithms.
Due to the widespread use of mobile robots in various applications, the path planning problem has emerged as one of the important research topics. Path planning is defined as finding the shortest path starting from the initial point to the destination in such a way as to get rid of the obstacles it encounters. In this study, we propose a path planning algorithm based on a teaching-learning-based optimization (TLBO) algorithm with Bezier curves in a static environment with obstacles. The proposed algorithm changes the initially randomly selected control points step by step to obtain shorter Bezier curves that do not hit obstacles. We also improve the genetic algorithm-based path planning algorithm. Experimental results show that they provide better paths than other existing algorithms.
DOI : 10.14736/kyb-2024-3-0293
Classification : 68T40, 68W25, 78M50
Keywords: path planning; mobile robot; teaching-learning based optimization; Bezier curve 
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     title = {An effective global path planning algorithm with teaching-learning-based optimization},
     journal = {Kybernetika},
     pages = {293--316},
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     language = {en},
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Hazrati Nejad, Emad; Yigit-Sert, Sevgi; Emrah Amrahov, Şahin. An effective global path planning algorithm with teaching-learning-based optimization. Kybernetika, Tome 60 (2024) no. 3, pp. 293-316. doi: 10.14736/kyb-2024-3-0293

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