Abstract
In this study, various chromosome coding methods are analyzed for genetic algorithm to solve path planning problem of mobile robots. Path planning tries to find a feasible path for mobile robots to move from a starting node to a target node in an environment with obstacles. Genetic algorithms have been widely used to generate an optimal path by taking the advantage of its strong optimization ability. Binary, decimal and orderly numbered grids coding methods are used to create chromosomes in this study. Path distance, generation number and solution time parameters are observed and compared for the three coding methods under the same conditions. Results showed that the solution time is directly affected by chromosome coding method.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Hu, Y., Yang, S.X.: A knowledge based genetic algorithm for path planning of a mobile robot. In: Proceedings of the 2004 IEEE, International Conference on Robotics and Automation, vol. 5, pp. 4350–4355 (2004)
Tu, J., Yang, S.X.: Genetic Algorithm based path planning for a mobile robot. In: Proceedings. ICRA ‘03. IEEE International Conference on Robotics and Automation, vol. 1, pp. 1221–1226 (2003)
Al-Taharva, I., Sheta, A., Al-Weshah, M.: A mobile robot path plannig using genetic algorithm in static environment. J. Comput. Sci. 4, 341–344 (2008)
Elshamli, A., Abdullah, H.A., Areibi, S.: Genetic algorithm for dynamic path planning. Canadian Conference on Electrical and Computer Engineering 2, 677–680 (2004)
Manikas, T.W., Ashenayi, K., Wainwright, R.L.: Genetic algorithms for autonomous robot navigation. Instrumentation and Measurement Magazine, IEEE 10, 26–31 (2007)
Naderan-Tahan, M., Manzuri-Shalmani, M.T.: Efficient and safe path planning for a mobile robot using genetic algorithm. CEC ‘09. IEEE Congress on Evolutionary Computation, pp. 2091–2097 (2009)
Yao, Z., Ma, L.: A static environment-based path planning method by using genetic algorithm. International Conference on Computing, Control and Industrial Engineering (CCIE), vol. 2, pp. 405–407 (2010)
Li, Q., Zhang, W., Yin, Y., Wang, Z., Liu, G.: An improved genetic algorithm of optimum path planning for mobile robots. ISDA ‘06. Sixth International Conference on Intelligent Systems Design and Applications, vol. 2, pp. 637–642 (2006)
Gelenbe, E., Liu, P., Lainé, J.: Genetic algorithms for route discovery. IEEE Transactions on Systems, Man, and Cybernetics. Part B: Cybernetics 36, 1247–1254 (2006)
Sugihara, K., Smith, J.: Genetic algorithms for adaptive motion planning of an autonomous mobil robot. In: Proceedings, IEEE International Symposium on Computational Intelligence in Robotics and Automation, CIRA’97, pp. 138–143 (1997)
Nagib, G., Gharieb, W.: Path planning for a mobile robot using genetic algorithms. ICEEC ‘04, International Conference on Electrical, Electronic and Computer Engineering, pp. 185–189 (2004)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag London Limited
About this paper
Cite this paper
Tuncer, A., Yildirim, M. (2011). Chromosome Coding Methods in Genetic Algorithm for Path Planning of Mobile Robots. In: Gelenbe, E., Lent, R., Sakellari, G. (eds) Computer and Information Sciences II. Springer, London. https://doi.org/10.1007/978-1-4471-2155-8_48
Download citation
DOI: https://doi.org/10.1007/978-1-4471-2155-8_48
Published:
Publisher Name: Springer, London
Print ISBN: 978-1-4471-2154-1
Online ISBN: 978-1-4471-2155-8
eBook Packages: EngineeringEngineering (R0)