Skip to main content
SpringerLink
Log in

Comparing Modified PSO Algorithms for MRS in Unknown Environment Exploration

  • Conference paper
  • First Online:
Advances in Information and Communication Technology (ICTA 2016)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 538))

  • 1157 Accesses

Abstract

Multi-robot systems (MRS) have shown clear advantages over single robots in the application of exploring unknown environments - a fundamental problem in robotics. Among algorithms which are able to be applied to MRS in the application, Particle Swarm Optimization (PSO) - a heuristic optimization technique inspired by social behavior of natural swarms - has received much attention and is well-known for its efficiency and simplicity to implement. However, when conventional PSO is applied, the problems of disconnection and collision within the system are inevitable. Two of various methods proposed to address these crucial issues are applying BOIDS and Artificial Potential Field (APF) to modify PSO. In this work, we simulated both modified algorithms on Matlab under various scenarios for analysis and comparison.

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

Access this chapter

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 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

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Farinelli, A., Iocchi, L., Nardi, D.: Multirobot systems: a classification focused on coordination. IEEE Trans. Syst. Man Cybern. Part B (Cybern.) 34(5), 2015–2028 (2004)

    Article  Google Scholar 

  2. Robin, M., Blitch, J., Casper, J.: AAAI/RoboCup-2001 Urban Search and Rescue Events. AI Magazine 23, no. 1: 37 (2002)

    Google Scholar 

  3. Couceiro, M.S., Rocha, R.P., Ferreira, N.M.: A novel multi-robot exploration approach based on particle swarm optimization algorithms. In: 2011 IEEE International Symposium on Safety, Security, and Rescue Robotics, pp. 327–332. IEEE, November 2011

    Google Scholar 

  4. Kennedy, J.: Particle swarm optimization. In: Encyclopedia of Machine Learning, pp. 760–766. Springer, US (2011)

    Google Scholar 

  5. Reynolds, C.W.: Flocks, herds and schools: a distributed behavioral model. ACM SIGGRAPH Comput. Graph. 21(4), 25–34 (1987)

    Article  Google Scholar 

  6. Khatib, O.: Real-time obstacle avoidance for manipulators and mobile robots. Int. J. Robot. Res. 5(1), 90–98 (1986)

    Article  MathSciNet  Google Scholar 

  7. Paulos, E.: On-line collision avoidance for multiple robots using b-splines. University of California, Berkeley, Computer Science Division (1998)

    Google Scholar 

  8. Kumar, R.A., Menon, A.: Collision avoidance in a multi-robot system by emulating human behaviour. In: International Conference on Information Systems Analysis and Synthesis and World Multiconference on Systemics, June 2001

    Google Scholar 

  9. Sharma, S., Tiwari, R.: A survey on multi robots area exploration techniques and algorithms. In: 2016 International Conference on Computational Techniques in Information and Communication Technologies (ICCTICT), pp. 151–158. IEEE, March 2016

    Google Scholar 

  10. Balch, T., Hybinette, M.: Social potentials for scalable multi-robot formations. In: Proceedings of the IEEE International Conference on Robotics and Automation, ICRA 2000, vol. 1, pp. 73–80. IEEE (2000)

    Google Scholar 

  11. Guanghua, W., Deyi, L., Wenyan, G., Peng, J.: Study on formation control of multi-robot systems. In: 2013 Third International Conference on Intelligent System Design and Engineering Applications (ISDEA), pp. 1335–1339. IEEE, January 2013

    Google Scholar 

  12. Lee, L.F., Bhatt, R., Krovi, V.: Comparison of alternate methods for distributed motion planning of robot collectives within a potential field framework. In: Proceedings of the 2005 IEEE International Conference on Robotics and Automation, pp. 99–104. IEEE, April 2005

    Google Scholar 

  13. Hoang, A.Q.: Simulating Hybrid BOIDS-PSO Algorithm for MRS in Unknown Environment Exploration. (Unpublished bachelor thesis) VNU University of Engineering and Technology, Hanoi, Vietnam (2015)

    Google Scholar 

  14. Hoang, A.Q., Pham, M.T.: Light source detection using multirobot systems with particle swarm optimization approach. In: The 3rd Vietnam Conference on Automation and Control (2015)

    Google Scholar 

  15. Hoang, A.-Q., Pham, M.-T.: Swarm intelligence-based approach for macroscopic scale odor source localization using multi-robot system. In: Akagi, M., et al. (eds.) Advances in Information and Communication Technology. AISC, vol. 538, pp. 593–602. Springer, Switzerland (2016)

    Google Scholar 

Download references

Acknowledgments

This work has been supported by Vietnam National University, Hanoi (VNU), under Project No. QG.15.25.

Author information

Authors and Affiliations

  1. VNU University of Engineering and Technology, 144 Xuan Thuy, Cau Giay, Hanoi, Vietnam

    Anh-Quy Hoang & Minh-Trien Pham

Authors
  1. Anh-Quy Hoang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Minh-Trien Pham
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Anh-Quy Hoang or Minh-Trien Pham .

Editor information

Editors and Affiliations

  1. School of Information Science、Area of Human Life Design , Japan Advanced Institute of Science and Technology, Nomi-shi, Ishikawa, Japan

    Masato Akagi

  2. Department of Computer Science, VNU University of Engineering and Technology, Hanoi, Vietnam

    Thanh-Thuy Nguyen

  3. Faculty of Information Technology, Thai Nguyen University of Information and Communication Technology, Thai Nguyen, Vietnam

    Duc-Thai Vu

  4. Thai Nguyen University of Information and Communication Technology, Thai Nguyen, Vietnam

    Trung-Nghia Phung

  5. School of Knowledge Science、Area of Knowledge Management , Japan Advanced Institute of Science and Technology, Nomi-shi, Ishikawa, Japan

    Van-Nam Huynh

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this paper

Cite this paper

Hoang, AQ., Pham, MT. (2017). Comparing Modified PSO Algorithms for MRS in Unknown Environment Exploration. In: Akagi, M., Nguyen, TT., Vu, DT., Phung, TN., Huynh, VN. (eds) Advances in Information and Communication Technology. ICTA 2016. Advances in Intelligent Systems and Computing, vol 538. Springer, Cham. https://doi.org/10.1007/978-3-319-49073-1_23

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-49073-1_23

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-49072-4

  • Online ISBN: 978-3-319-49073-1

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation