Skip to main content

A Modified Real Time A* Algorithm and Its Performance Analysis for Improved Path Planning of Mobile Robot

  • Conference paper
  • First Online:
Computational Intelligence in Data Mining - Volume 2

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 32))

Abstract

This paper proposed an online path planning of mobile robot in a grid-map environment using modified real time A* algorithm. This algorithm has implemented in simulated and Khepera-II environment and find the optimized path from an initial predefine position to a predefine target position by avoiding the obstacles in its trajectory of path. The path finding strategy is designed in a grid-map and cluttered environment with static and dynamic obstacles with quadrant concept. The optimization the path is found using this algorithm as the goal is present in any of the four quadrant and restricted the movement of the robot to only one quadrant. Robot will plan an optimal path by avoiding obstructions in its way and minimizing time, energy, and distance as the cost, but the original A* algorithm find the shortest path not optimized. Finally, it is compared with other heuristic algorithms.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover 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

Institutional subscriptions

References

  1. Bien, Z., Lee, J.: A minimum-time trajectory planning method for two robots. IEEE Trans. Robot. Autom. 8, 443–450 (2004)

    Google Scholar 

  2. Moll, M., Kavraki, L.E.: Path planning for minimal energy curves of constant length. In: Proceedings of IEEE International Conference on Robotics and Automation, pp. 2826–2831 (2004)

    Google Scholar 

  3. Qu, D., Du, Z., Xu, D., Xu, F.: Research on path planning for a mobile robot. Robot 30, 97–101 (2008)

    Google Scholar 

  4. Peng, Q.J., Kang, X.M., Zhao, T.T.: Effective virtual reality based building navigation using dynamic loading and path optimization. Int. J. Autom. Comput. 6, 335–343 (2009)

    Article  Google Scholar 

  5. Florczyk, S.: Robot Vision Video-Based Indoor Exploration with Autonomous and Mobile Robots. WILEY-VCH Verlag GmbH & Co.KGaA, Weinheim (2005)

    Google Scholar 

  6. Xiao, J., Michalewicz, Z., Zhang, L., Trojanowski, K.: Adaptive evolutionary planner/navigator for mobile robots. IEEE Trans. Evol. Comput. 1, 18–28 (1997)

    Google Scholar 

  7. LaVall, S.M.: Planning Algorithms. Cambridge University Press, Cambridge (2010). Available: http://msl.cs.uiuc.edu/planning

  8. Liu, X., Gong, D.: A comparative study of A-star algorithms for search and rescue in perfect maze. In: International Conference on Electric Information and Control Engineering (ICEICE), pp. 24–27 (2011)

    Google Scholar 

  9. Ma, C., Diao, A., Chen, Z., Qi, B.: Study on the hazardous blocked synthetic value and the optimization route of hazardous material transportation network based on A-star algorithm. In: 7th International Conference on Natural Computation, vol. 4, pp. 2292–2294 (2011)

    Google Scholar 

  10. Castillo, O., Trujillo, L.: Multiple objective optimization genetic algorithms for path planning in autonomous mobile robots. Int. J. Comput. Syst. Signals 6 (2005)

    Google Scholar 

  11. Liu, C., Liu, H., Yang, J.: A path planning method based on adaptive genetic algorithm for mobile robot. J. Inf. Comput. Sci. 8(5), 808–814 (2011)

    Google Scholar 

  12. Taharwa, A.L., Sheta, A.M., Weshah, A.I.: A mobile robot path planning using genetic algorithm in static environment. J. Comput. Sci. 4, 341–344 (2008)

    Google Scholar 

  13. Konar, A.: Artificial Intelligence and Soft Computing: Behavioral and Cognitive Modeling of the Human Brain, 1st edn. CRC Press, Boca Raton (1999)

    Google Scholar 

  14. Wei, X.: Robot path planning based on simulated annealing and artificial neural networks. Res. J. Appl. Sci. Eng. Technol. 6, 149–155 (2013)

    Google Scholar 

  15. Das, A., Mohapatra, P., Mishra, P., Das, P.K., Mandhata, S.C.: Improved real time A* algorithm for path planning of mobile robot in quadrant based environment. Int. J. Adv. Comput. Theory Eng. 1, 25–30 (2012)

    Google Scholar 

  16. Das, P.K., Pradhan, S.K., Patro, S.N., Balabantaray, B.K.: Artificial immune system based path planning of mobile robot. In: Soft Computing Techniques in Vision Science, vol. 395, pp. 195–207. Springer, Berlin (2012)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to P. K. Das .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer India

About this paper

Cite this paper

Das, P.K., Behera, H.S., Pradhan, S.K., Tripathy, H.K., Jena, P.K. (2015). A Modified Real Time A* Algorithm and Its Performance Analysis for Improved Path Planning of Mobile Robot. In: Jain, L., Behera, H., Mandal, J., Mohapatra, D. (eds) Computational Intelligence in Data Mining - Volume 2. Smart Innovation, Systems and Technologies, vol 32. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2208-8_21

Download citation

  • DOI: https://doi.org/10.1007/978-81-322-2208-8_21

  • Published:

  • Publisher Name: Springer, New Delhi

  • Print ISBN: 978-81-322-2207-1

  • Online ISBN: 978-81-322-2208-8

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics