Skip to main content
SpringerLink
Log in
Book cover

The International Conference on Advances in Emerging Trends and Technologies

ICAETT 2019: Advances in Emerging Trends and Technologies pp 432–441Cite as

Path Planning for Mobile Robot Based on Cubic Bézier Curve and Adaptive Particle Swarm Optimization (A2PSO)

  • Conference paper
  • First Online:

  • 823 Accesses

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1066))

Abstract

In this work, a new approach is proposed for getting a solution of path-planning for mobile robot based on cubic Bézier curve and adaptive particle swarm optimization (A2PSO). Paths generated using a cubic Bézier curve are optimized globally through the A2PSO algorithm. The A2PSO algorithm is significantly more powerful than conventional PSO algorithm. Our approach was successful in determining the shortest path in several environments full of obstacles compared to the performance of the conventional PSO.

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. Pérez, L.H., Mora Aguilar, M.C., Sánchez, N.M., Montesinos, A.F.: Path planning based on parametric curves, chapter 7, pp. 125–143. InTech, September 2018

    Google Scholar 

  2. Costanzi, R., Fanelli, F., Meli, E., Ridolfi, A., Allotta, B.: Generic path planning algorithm for mobile robots based on Bézier curves. IFAC-PapersOnLine 49(15), 145–150 (2016). 9th IFAC Symposium on Intelligent Autonomous Vehicles IAV 2016

    Article  Google Scholar 

  3. Ravankar, A., Ravankar, A., Kobayashi, Y., Hoshino, Y., Peng, C.-C.: Path smoothing techniques in robot navigation: state-of-the-art, current and future challenges. Sensors 18(9), 3170 (2018)

    Article  Google Scholar 

  4. Elbanhawi, M., Simic, M., Jazar, R.N.: Continuous path smoothing for car-like robots using B-Spline curves. J. Intell. Robot. Syst. 80(1), 23–56 (2015)

    Article  Google Scholar 

  5. Nie, Z., Yang, X., Gao, S., Zheng, Y., Wang, J., Wang, Z.: Research on autonomous moving robot path planning based on improved particle swarm optimization. In: 2016 IEEE Congress on Evolutionary Computation (CEC), pp. 2532–2536, July 2016

    Google Scholar 

  6. Zafar, M.N., Mohanta, J.C.: Methodology for path planning and optimization of mobile robots: a review. Procedia Comput. Sci. 133, 141–152 (2018). International Conference on Robotics and Smart Manufacturing (RoSMa 2018)

    Article  Google Scholar 

  7. Dewang, H.S., Mohanty, P.K., Kundu, S.: A robust path planning for mobile robot using smart particle swarm optimization. Procedia Comput. Sci. 133, 290–297 (2018)

    Article  Google Scholar 

  8. Saska, M., Macas, M., Preucil, L., Lhotska, L.: Robot path planning using particle swarm optimization of Ferguson splines. In: 2006 IEEE Conference on Emerging Technologies and Factory Automation, pp. 833–839, September 2006

    Google Scholar 

  9. Arana-Daniel, N., Gallegos, A.A., López-Franco, C., Alanis, A.Y.: Smooth global and local path planning for mobile robot using particle swarm optimization, radial basis functions, splines and Bézier curves. In: 2014 IEEE Congress on Evolutionary Computation (CEC), pp. 175–182, July 2014

    Google Scholar 

  10. Li, G., Wusheng, C.: Path planning for mobile robot using self-adaptive learning particle swarm optimization. Sci. China Inf. Sci. 61(5), 052204 (2018)

    Article  MathSciNet  Google Scholar 

  11. Tharwat, A., Elhoseny, M., Hassanien, A.E., Gabel, T., Kumar, A.: Intelligent Bézier curve-based path planning model using Chaotic Particle Swarm Optimization algorithm. Cluster Comput. 1–22 (2018)

    Google Scholar 

  12. Liang, J.J., Song, H., Qu, B.Y., Liu, Z.F.: Comparison of three different curves used in path planning problems based on particle swarm optimizer. Math. Prob. Eng. 2014, 1–15 (2014)

    Google Scholar 

  13. Soto, D., Soto, W.: A parallel adaptive PSO algorithm with non-iterative electrostatic repulsion and social dynamic neighborhood. In: Madureira, A., Abraham, A., Gamboa, D., Novais, P. (eds.) Intelligent Systems Design and Applications, pp. 570–581. Springer, Cham (2017)

    Chapter  Google Scholar 

  14. Gaillard, F.: Approche cognitive pour la planification de trajectoire sous contraintes. Ph.D. thesis, Université des Sciences et Technologie de Lille - Lille I (2012)

    Google Scholar 

  15. Connors, J., Elkaim, G.: Analysis of a spline based, obstacle avoiding path planning algorithm. In: 2007 IEEE 65th Vehicular Technology Conference - VTC2007-Spring, pp. 2565–2569, April 2007

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Universidad de Antioquia, Medellí­n, Colombia

    Daniel Soto

  2. Universidad Católica de Pereira, Pereira, Colombia

    Wilson Soto

Authors
  1. Daniel Soto
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Wilson Soto
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Wilson Soto .

Editor information

Editors and Affiliations

  1. Eindhoven University of Technology, Eindhoven, Noord-Brabant, The Netherlands

    Miguel Botto-Tobar

  2. Universidad Técnica de Babahoyo, Babahoyo, Ecuador

    Joffre León-Acurio

  3. Universitat de Valencia, Valencia, Valencia, Spain

    Angela Díaz Cadena

  4. Centro de Investigación y Desarrollo Profesional, Babahoyo, Los Rios Province, Ecuador

    Práxedes Montiel Díaz

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Soto, D., Soto, W. (2020). Path Planning for Mobile Robot Based on Cubic Bézier Curve and Adaptive Particle Swarm Optimization (A2PSO). In: Botto-Tobar, M., León-Acurio, J., Díaz Cadena, A., Montiel Díaz, P. (eds) Advances in Emerging Trends and Technologies. ICAETT 2019. Advances in Intelligent Systems and Computing, vol 1066. Springer, Cham. https://doi.org/10.1007/978-3-030-32022-5_40

Download citation

Publish with us

Policies and ethics

Search

Navigation