Feasibility Analysis of Path Planning Algorithms

Allozi E., Yılmaz A., Ervan O., Temeltaş H.

16th International Conference on INnovations in Intelligent SysTems and Applications, INISTA 2022, Biarritz, France, 8 - 12 August 2022 identifier

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.1109/inista55318.2022.9894241
  • City: Biarritz
  • Country: France
  • Keywords: Feasibility Analysis, Mobile Robots, Neural Networks, Path Planning, Shortness, Smoothness, Traceability
  • Istanbul Technical University Affiliated: Yes


© 2022 IEEE.Path planning, which aims to find the most suitable route between source and destination, is a challenging problem in mobile robotics. Although there are several study ideas on the path planning challenges of mobile robots in the literature, there is no approach that evaluates path quality qualitatively and quantitatively. It is significant to choose the optimal path by analyzing the properties of the path and the planning algorithm for effectiveness and efficiency. In this paper, we proposed a feasibility analysis to evaluate the quality of the path planning algorithm from various perspectives. This paper defines criteria for path planning algorithms and investigates traceability, smoothness, and shortness factors. Furthermore, by using these test results, a novel artificial neural network-based method has been proposed to enhance path planning algorithms without altering them.