Coverage with a Team of Wheeled Mobile Robots

Abstract

This article presents a control system enabling coverage of a prescribed ground area by a team of wheeled mobile robots. The control system relies on equal balancing of the costs among the wheeled robots. Cost balancing leverages the intuition that a healthy neighbor could help a degraded robot to carry out its monitoring task simply by moving slightly towards the degraded robot. This feature allows the control system to support situations where vehicles have varying sensor characteristics. The article focuses on the design of the system and the results of experiments obtained with a small number of networked ground robots. The coverage control system is decentralized. Hence, no element of the system is a single point of failure, and the computations can be distributed. The experiments show (1) the satisfactory, yet suboptimal, performance of the coverage control system under healthy conditions, and the adaptation of the vehicles in case a team member is subject to a degraded condition of operation, and (2) the feasibility of the integration of the coverage control system with low-cost commercial wheeled mobile robot systems.

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References

  1. 1.

    Rabbath, C.A., Léchevin, N.: Safety and Reliability in Cooperating Unmanned Aerial Systems. World Scientific Publishing (2010)

  2. 2.

    Smith, S.L., Schwager, M., Rus, D.: Persistent tasks for robots in changing environments. IEEE Transactions on Robotics, pp. 1–14 (2010)

  3. 3.

    Cortés, J., Martinez, S., Karatas, T., Bullo, F.: Coverage control for mobile sensing networks. IEEE Trans. Robot. Autom. 20(2), 243–255 (2004)

    Article  Google Scholar 

  4. 4.

    Cortes, J., Martinez, S., Bullo, F.: Spatially-distributed coverage optimization and control with limited-range interactions. ESAIM: Control Optimisation Calc Var 11(4), 691–719 (2005)

    Article  MATH  MathSciNet  Google Scholar 

  5. 5.

    Stergiopoulos, Y., Tzes, A.: Convex voronoi-inspired space partitioning for heterogeneous networks: a coverage-oriented approach. Control Theory Appl. IET 4(12), 2802–2812 (2010)

    Article  MathSciNet  Google Scholar 

  6. 6.

    Schwager, M., Julian, B., Angermann, M., Rus, D.: Eyes in the sky: decentralized control for the deployment of robotic camera networks. In: Proceedings of the IEEE (2010)

  7. 7.

    Wang, Y., Hussein, I.I.: Awareness coverage control over large-scale domains with intermittent communications. IEEE Trans. Autom. Control 55(8), 1850–1859 (2010). doi:10.1109/TAC.2010.2042346

    Article  MathSciNet  Google Scholar 

  8. 8.

    Marier, J.-S., Rabbath, C.-A., Léchevin, N.: Optimizing the location of sensors subject to health degradation. In: American Control Conference, pp. 3760–3765 (2011)

  9. 9.

    Marier, J.-S., Rabbath, C.A., Léchevin, N.: Placement of a team of surveillance vehicles subject to navigation failures. In: AIAA Guidance, Navigation, and Control Conference, pp. AIAA 2011–6476. AIAA (2011)

  10. 10.

    Suzuki, A., Drezner, Z.: The p-center location problem in an area. Locat. Sci. 4(1–2), 69–82 (1996)

    Article  MATH  Google Scholar 

  11. 11.

    Aurenhammer, F.: Voronoi diagrams—a survey of a fundamental geometric data structure. ACM Comput. Surv. 23(3), 345–405 (1991)

    Article  Google Scholar 

  12. 12.

    Aurenhammer, F.: Power diagrams: properties, algorithms and applications. SIAM J. Comput. 16(1), 78–96 (1987)

    Article  MATH  MathSciNet  Google Scholar 

  13. 13.

    Cortés, J.: Coverage optimization and spatial load balancing by robotic sensor networks. IEEE Trans. Autom. Control 55(3), 749–754 (2010)

    Article  Google Scholar 

  14. 14.

    Pimenta, L., Schwager, M., Lindsey, Q., Kumar, V., Rus, D., Mesquita, R., Pereira, G.: Simultaneous coverage and tracking (SCAT) of moving targets with robot networks. Algorithmic Foundation of Robotics VIII, pp. 85–99 (2009)

  15. 15.

    Schwager, M.: A gradient optimization approach to adaptive multi-robot control. Ph.D. thesis, Massachusetts Institute of Technology (2009)

  16. 16.

    Lloyd, S.: Least squares quantization in PCM. IEEE Trans. Inf. Theory 28(2), 129–137 (1982)

    Article  MATH  MathSciNet  Google Scholar 

  17. 17.

    Olfati-Saber, R., Fax, J.A., Murray, R.M.: Consensus and cooperation in networked multi-agent systems. Proc. IEEE 95(1), 215–233 (2007)

    Article  Google Scholar 

  18. 18.

    Hines, W.W., Montgomery, D.C.: Probability and Statistics in Engineering and Management Science. Wiley, New York (1980)

    Google Scholar 

  19. 19.

    Quanser Inc: http://www.quanser.com

  20. 20.

    Koditschek, D.E., Rimon, E.: Robot navigation functions on manifolds with boundary. Adv. Appl. Math. 11(4), 412–442 (1990)

    Article  MATH  MathSciNet  Google Scholar 

  21. 21.

    NaturalPoint, Inc.: Optitrack flex:v100r2 (2011). http://www.naturalpoint.com/optitrack/products/flex-v100r2/. Accessed 17 June 2011

  22. 22.

    Quanser Consulting Inc.: Quanser – control solutions – control design software quarcⒸ2.1. http://www.quanser.com/english/html/solutions/fs_soln_software.html. Accessed 17 June 2011 (2011)

  23. 23.

    Gumstix Inc.: http://www.gumstix.com/. Accessed 18 July 2012 (2012)

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Correspondence to C. A. Rabbath.

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Rabbath, C.A., Léchevin, N. Coverage with a Team of Wheeled Mobile Robots. J Intell Robot Syst 78, 553–575 (2015). https://doi.org/10.1007/s10846-014-0031-z

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Keywords

  • Coverage
  • Voronoi coverage
  • Optimization
  • Wheeled mobile robots
  • Experiments
  • Cooperative control
  • Health management