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Heuristic Coordination for Multi-agent Motion Planning

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International Conference on Innovative Computing and Communications

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1087))

Abstract

Fuzzy logic and potential field methods are competent techniques for autonomous mobile robot navigation. In this paper, a conventional potential field-based scheme for multi-agent motion planning has been presented along with a genetic-fuzzy-based navigation scheme for off-line performance comparison. They are used to generate decision against collision in the best possible manner. The potential field method (PFM) relies on its potential function and GA-Fuzzy works based on its knowledge base. Initially, the number of robots is taken as eight; later on, it is increased to 12. The necessity of the coordination scheme is more for a larger number of robots. Finally, the performances of those two approaches are compared to solve 100 test cases. GA-Fuzzy-based motion planner has shown adaptive in comparison to the PFM.

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References

  1. A. Mackworth, On seeing robots. Comput. Vis. Syst. Theory Appl. 1–13 (1993)

    Google Scholar 

  2. M. Asada, H. Kitano, I. Noda, M. Veloso, Robocup: today and tomorrow—what we have and learned. Artif. Intell. 110, 193–214 (1999)

    Article  Google Scholar 

  3. J.H. Kim, Y.J. Kim, D.H. Kim, K.T. Seow, Soccer Robotics. Springer Tracts in Advanced Robotics, vol. 11 (Springer-Verlag Berlin Heidelberg, 2004)

    Book  Google Scholar 

  4. S. Buck, U. Weber, M. Beetz, T. Schmitt, Multi robot path planning for dynamic environments: a case study (IEEE/RSJIROS Conf, Wailea, USA, 2001)

    Google Scholar 

  5. J.C. Latombe, Robot motion planning. The Springer International Series in Engineering and Computer Science. vol. 124 (Springer US, 1991)

    Google Scholar 

  6. N.B. Hui, Coordinated motion planning of multiple mobile robots using potential field method, in International Conference on Industrial Electronics, Control and Robotics (IECR 2010) (NIT Rourkela, India, 2010)

    Google Scholar 

  7. B. Pradhan, D.S. Roy, N.B. Hui, Motion planning and coordination of multi-agent systems. Int. J. Comput. Vis. Robot. 8, 492–508 (2018)

    Article  Google Scholar 

  8. N.B. Hui, V. Mahendar, D.K. Pratihar, Time-optimal collision free navigation of a car-like robot using a neuro-fuzzy approach. Fuzzy Sets Syst. 157, 2171–2204 (2006)

    Article  Google Scholar 

  9. F. Abdessemed, K. Benmahammed, E. Monacelli, A Fuzzy-based reactive controller for a non-holonomic mobile robot. Robot. Autonom. Syst. 47, 31–46 (2004)

    Article  Google Scholar 

  10. T. Fraichard, P. Garnier, Fuzzy control to drive car-like vehicles. Robot. Autonom. Systems 34, 1–22 (2001)

    Article  Google Scholar 

  11. J.H. Park, D. Stonier, J.H. Kim, B.H. Ahn, M.G. Jeon, Recombinant rule selection in evolutionary algorithm for Fuzzy path planner of robot soccer, in KI 2006: Advances in Artificial Intelligence. KI 2006 ed. by C. Freksa, M. Kohlhase, K. Schill. Lecture Notes in Computer Science, vol. 4314 (Springer, Berlin, Heidelberg, 2007)

    Google Scholar 

  12. B. Pradhan, V. Vijayakumar, N.B. Hui, D.S. Roy, Intelligent navigation of multiple coordinated robots. J. Intell. Fuzzy Syst. (IOS Press, 2019). https://doi.org/10.3233/jifs-169996

    Article  Google Scholar 

  13. B. Pradhan, D.S. Roy, N.B. Hui, Multi-agent Navigation and Coordination Using GA-Fuzzy Approach, in Soft Computing for Problem Solving. Advances in Intelligent Systems and Computing ed. by J. Bansal, K. Das, A. Nagar, K. Deep, A. Ojha, vol. 817 (Springer, Singapore, 2019)

    Google Scholar 

  14. S. Thrun, An approach to learning mobile robot navigation. Robot. Auton. Syst. 15, 301–309 (1996)

    Article  Google Scholar 

  15. D.K. Pratihar, Soft Computing: Fundamentals and Applications (Alpha Science International Limited, 2015)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Mechanical Engineering, National Institute of Technology Durgapur, Durgapur, India

    Buddhadeb Pradhan & Nirmal Baran Hui

  2. Department of Computer Science and Engineering, National Institute of Technology Meghalaya, Shillong, India

    Diptendu Sinha Roy

Authors
  1. Buddhadeb Pradhan
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  2. Nirmal Baran Hui
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  3. Diptendu Sinha Roy
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Corresponding author

Correspondence to Buddhadeb Pradhan .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Maharaja Agrasen Institute of Technology, New Delhi, Delhi, India

    Ashish Khanna

  2. Department of Computer Science and Engineering, Maharaja Agrasen Institute of Technology, New Delhi, Delhi, India

    Deepak Gupta

  3. Department of Computer Science and Engineering, Christ University, Bangalore, India

    Siddhartha Bhattacharyya

  4. Department of Computer Science, VŠB—Technical University of Ostrava, Ostrava, Czech Republic

    Vaclav Snasel

  5. Department of Computer Science, VŠB—Technical University of Ostrava, Ostrava, Czech Republic

    Jan Platos

  6. Faculty of Computers and Information, Cairo University, Giza, Egypt

    Aboul Ella Hassanien

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Pradhan, B., Hui, N.B., Roy, D.S. (2020). Heuristic Coordination for Multi-agent Motion Planning. In: Khanna, A., Gupta, D., Bhattacharyya, S., Snasel, V., Platos, J., Hassanien, A. (eds) International Conference on Innovative Computing and Communications. Advances in Intelligent Systems and Computing, vol 1087. Springer, Singapore. https://doi.org/10.1007/978-981-15-1286-5_49

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