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Tracking multiple moving targets with swarms of mobile robots

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Abstract

This paper presents a distributed approach to enable mobile robot swarms to track multiple targets moving unpredictably. The proposed approach consists of two constituent algorithms: local interaction and target tracking. When the robots are faster than the targets, Lyapunov theory can be applied to show that the robots converge asymptotically to each vertex of the desired equilateral triangular configurations while tracking the targets. Toward practical implementation of the algorithms, it is important to realize the observation capability of individual robots in an inexpensive and efficient way. A new proximity sensor that we call dual rotating infrared (DRIr) sensor is developed to meet these requirements. Both our simulation and experimental results employing the proposed algorithms and DRIr sensors confirm that the proposed distributed multi-target tracking method for a swarm of robots is effective and easy to implement.

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References

  1. Choset H (2001) Coverage for robotics—a survey of recent results. Ann Math Artif Intell 31(1–4): 113–126

    Article  Google Scholar 

  2. Sahin E (2005) Swarm robotics: from sources of inspiration to domains of application. In: Proceedings of 8th international conference on the simulation of adaptive behavior. LNCS, vol 3342, pp 10–20

  3. Zarzhitsky D, Spears D, Spears W (2005) Distributed robotics approach to chemical plume tracing. In: Proceedings of IEEE/RSJ international conferene on intelligent robots and systems, pp 4034–4039

  4. Jatmiko W, Sekiyama K, Fukuda T (2007) A particle swarm-based mobile sensor network for odor source localization in a dynamic environment. In: Gini M, Voyles R (eds) Distributed autonomous robotic systems, vol 7. Springer, Japan, pp 71–80

    Google Scholar 

  5. Hayes AT, Martinoli A, Goodman RM (2003) Swarm robotic odor localization: off-line optimazation and validation with real robots. Robotica 21(4): 427–441

    Article  Google Scholar 

  6. Dhariwal A, Sukhatme GS, Requicha AAG (2004) Bacterium-inspired robots for environmental monitoring. In: Proceedings of IEEE international conference on robotics and automation, pp 1436–1443

  7. Spletzer JR, Taylor CJ (2003) Dynamic sensor planning and control for optimally tracking targets. Int J Robot Res 22(1): 7–20

    Article  Google Scholar 

  8. Jung B, Sukhatme GS (2002) Tracking targets using multiple robots: the effect of environment occlusion. Autonom Robots 13(3): 191–205

    Article  MATH  Google Scholar 

  9. Krishnanand KN, Amruth P, Guruprasad MH (2006) Glowworm-inspired robot swarm for simultaneous taxis towards multiple radiation sources. In: Proceedings of IEEE international conference on robotics and automation, pp 958– 963

  10. Kamath S, Meisner E, Isler V (2007) Triangulation based multi target tracking with mobile sensor networks. In: Proceedings of IEEE international conference on robotics and automation, pp 3283–3288

  11. Cui X, Hardin CT, Ragade RK, Elmaghraby AS (2004) A swarm approach for emission sources localization. In: Proceedings of 16th IEEE international conference on tools with artificial intelligence, pp 424–430

  12. Spears W, Spears D, Hamann J, Heil R (2004) Distributed, physics-based control of swarms of vehicles. Autonom Robots 17(2–3): 137–162

    Article  Google Scholar 

  13. Halliday D, Resnick R, Walker J (1997) Fundamentals of physics. 5th Ed. Wiley, New York

    Google Scholar 

  14. Lee G, Chong NY (2009) A geometric approach to deploying robot swarms. Ann Math Artif Intell 52(2–4): 257–280

    MathSciNet  Google Scholar 

  15. Zheng YF, Chen W (2007) Mobile robot team forming for crystallization of protein. Autonom Robots 23(1): 69–78

    Article  Google Scholar 

  16. Howard A, Mataric MJ, Sukhatme GS (2002) Mobile sensor network deployment using potential fields: a distributed, scalable solution to the area coverage problem. In: Proceedings of international symposium on distributed autonomous robotic systems, pp 299–308

  17. Fujibayashi K, Murata S, Sugawara K, Yamamura M (2002) Self-organizing formation algorithm for active elements. In: Proceedings of IEEE symposium on reliable distributed systems, pp 416–421

  18. McLurkin J, Smith J (2004) Distributed algorithms for dispersion in indoor environments using a swarm of autonomous mobile robots. In: Proceedings of international symposium on distributed autonomous robotic systems, pp 831–890

  19. Shucker B, Murphey TD, Bennett JK (2008) Convergence-preserving switching for topology-dependent decentralized systems. IEEE Trans Robot 24(6): 1405–1415

    Article  Google Scholar 

  20. Balch T, Hybinette M (2000) Social potentials for scalable multi-robot formations. In: Proceedings of IEEE international conference on robotics and automation, pp 73–80

  21. Reif J, Wang H (1999) Social potential fields: a distributed behavioral control for autonomous robots. Robot Autonom Syst 27(3): 171–194

    Article  Google Scholar 

  22. Martison E, Payton D (2005) Lattice formation in mobile autonomous sensor arrays. In: Proceedings of 8th international conference on the simulation of adaptive behavior, LNCS, vol 3342, pp 98– 111

  23. Heo N, Varshney PK (2003) A distributed self spreading algorithm for mobile wireless sensor networks. In: Proceedings of IEEE wireless communication and networking conference, pp 1597–1602

  24. Wang G-L, Cao G, Porta TL (2004) Movement-assisted sensor deployment. In: Proceedings of IEEE infocom conference, pp 2469–2479

  25. Ghosh S, Basu K, Das SK (2005) An architecture for next-generation radio access networks. IEEE Netw 19(5): 35–42

    Article  Google Scholar 

  26. Gurumohan PC, Hui J (2003) Topology design for free space optical networks. In: Proceedings of 12th international conference on computer communications and networks, pp 576–579

  27. Suzuki I, Yamashita M (1999) Distributed anonymous mobile robots: formation of geometric patterns. SIAM J Comput 28(4): 1347–1363

    Article  MATH  MathSciNet  Google Scholar 

  28. Dolev S (2000) Self-stabilization. MIT Press, Cambridge

    MATH  Google Scholar 

  29. Gonzalez RC, Woods RE (2002) Digital image processing. 2nd Ed. Prentice Hall, Englewood Cliffs

    Google Scholar 

  30. Slotine JE, Li W (1991) Applied nonlinear control. Prentice-Hall, Englewood Cliffs

    MATH  Google Scholar 

  31. Chen C-T (1999) Linear system theory and design. 3nd Ed. Oxford University Press, NY

    Google Scholar 

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Authors and Affiliations

  1. School of Information Science, Japan Advanced Institute of Science and Technology, 1-1 Asahidai, Nomi, Ishikawa, 923-1292, Japan

    Geunho Lee & Nak Young Chong

  2. College of Computing, Georgia Institute of Technology, Atlanta, GA, 30332, USA

    Henrik Christensen

Authors
  1. Geunho Lee
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  2. Nak Young Chong
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  3. Henrik Christensen
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Correspondence to Geunho Lee.

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Lee, G., Chong, N.Y. & Christensen, H. Tracking multiple moving targets with swarms of mobile robots. Intel Serv Robotics 3, 61–72 (2010). https://doi.org/10.1007/s11370-010-0059-2

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  • DOI: https://doi.org/10.1007/s11370-010-0059-2

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