AN EFFECTIVE GLOBAL PATH PLANNING ALGORITHM WITH TEACHING-LEARNING-BASED OPTIMIZATION


Nejad E. H., YİĞİT SERT S., EMRAH Ş.

Kybernetika, vol.60, no.3, pp.293-316, 2024 (SCI-Expanded) identifier

  • Publication Type: Article / Article
  • Volume: 60 Issue: 3
  • Publication Date: 2024
  • Doi Number: 10.14736/kyb-2024-3-0293
  • Journal Name: Kybernetika
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Linguistic Bibliography, zbMATH
  • Page Numbers: pp.293-316
  • Keywords: Bezier curve, mobile robot, path planning, teaching-learning based optimization
  • Ankara University Affiliated: Yes

Abstract

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.