Pattern-Based Genetic Algorithm Approach to Coverage Path Planning for Mobile Robots

  • Muzaffer Kapanoglu
  • Metin Ozkan
  • Ahmet Yazıcı
  • Osman Parlaktuna
Conference paper

DOI: 10.1007/978-3-642-01970-8_4

Part of the Lecture Notes in Computer Science book series (LNCS, volume 5544)
Cite this paper as:
Kapanoglu M., Ozkan M., Yazıcı A., Parlaktuna O. (2009) Pattern-Based Genetic Algorithm Approach to Coverage Path Planning for Mobile Robots. In: Allen G., Nabrzyski J., Seidel E., van Albada G.D., Dongarra J., Sloot P.M.A. (eds) Computational Science – ICCS 2009. ICCS 2009. Lecture Notes in Computer Science, vol 5544. Springer, Berlin, Heidelberg

Abstract

Sensor-based mobile robot coverage path planning (MRCPP) problem is a challenging problem in robotic management. We here develop a genetic algorithm (GA) for MRCPP problems. The area subject to coverage is modeled with disks representing the range of sensing devices. Then the problem is defined as finding a path which runs through the center of each disk at least once with minimal cost of full coverage. The proposed GA utilizes prioritized neighborhood-disk information to generate practical and high-quality paths for the mobile robot. Prioritized movement patterns are designed to generate efficient rectilinear coverage paths with no narrow-angle turn; they enable GA to find optimal or near-optimal solutions. The results of GA are compared with a well-known approach called backtracking spiral algorithm (BSA). Experiments are also carried out using P3-DX mobile robots in the laboratory environment.

Keywords

Genetic algorithms Coverage path planning Mobile robot 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Muzaffer Kapanoglu
    • 1
  • Metin Ozkan
    • 1
  • Ahmet Yazıcı
    • 1
  • Osman Parlaktuna
    • 1
  1. 1.College of EngineeringEskisehir Osmangazi UniversityEskisehirTurkey

Personalised recommendations