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Adaptive Inter-Robot Trust for Robust Multi-Robot Sensor Coverage

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Robotics Research

Part of the book series: Springer Tracts in Advanced Robotics ((STAR,volume 114))

Abstract

This paper proposes a new approach to both characterize inter-robot trust in multi-robot systems and adapt trust online in response to the relative performance of the robots. The approach is applied to a multi-robot coverage control scenario, in which a team of robots must spread out over an environment to provide sensing coverage. A decentralized algorithm is designed to control the positions of the robots, while simultaneously adapting their trust weightings. Robots with higher quality sensors take charge of a larger region in the environment, while robots with lower quality sensors have their regions reduced. Using a Lyapunov-type proof, it is proven that the robots converge to locally optimal positions for sensing that are as good as if the robots’ sensor qualities were known beforehand. The algorithm is demonstrated in Matlab simulations.

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References

  1. Breitenmoser, A., Schwager, M., Metzger, J.C., Siegwart, R., Rus, D.: Voronoi coverage of non-convex environments with a group of networked robots. In: IEEE International Conference on Robotics and Automation (ICRA), pp. 4982–4989. IEEE (2010)

    Google Scholar 

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

    Article  MathSciNet  Google Scholar 

  3. Cortes, 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. Drezner, Z.: Facility Location: A Survey of Applications and Methods. Springer Series in Operations Research. Springer, New York (1995)

    Book  Google Scholar 

  5. Du, Q., Faber, V., Gunzburger, M.: Centroidal Voronoi tessellations: applications and algorithms. SIAM Rev. 41(4), 637–676 (1999)

    Article  MathSciNet  MATH  Google Scholar 

  6. Godsil, C., Royle, G.: Algebraic Graph Theory. Graduate Texts in Mathematics. Springer, New York (2001)

    Book  MATH  Google Scholar 

  7. Horn, R.A., Johnson, C.R.: Matrix Analysis. Cambridge University Press, Cambridge (1990)

    MATH  Google Scholar 

  8. Khalil, H.: Nonlinear Systems. Prentice Hall PTR, Upper Saddle River (2002)

    MATH  Google Scholar 

  9. Kwok, A., Martinez, S.: Energy-balancing cooperative strategies for sensor deployment. In: 46th IEEE Conference on Decision and Control, pp. 6136–6141. IEEE (2007)

    Google Scholar 

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

    Google Scholar 

  11. Marier, J.S., Rabbath, C.A., Léchevin, N.: Health-aware coverage control with application to a team of small UAVs. IEEE Trans. Control Sys. Technol. 21, 1719–1730 (2012)

    Article  Google Scholar 

  12. Pavone, M., Arsie, A., Frazzoli, E., Bullo, F.: Equitable partitioning policies for robotic networks. In: IEEE International Conference on Robotics and Automation, ICRA’09, pp. 2356–2361. IEEE (2009)

    Google Scholar 

  13. Pimenta, L., Kumar, V., Mesquita, R.C., Pereira, G.: Sensing and coverage for a network of heterogeneous robots. In: 47th IEEE Conference on Decision and Control, CDC 2008, pp. 3947–3952. IEEE (2008)

    Google Scholar 

  14. Salapaka, S., Khalak, A., Dahleh, M.: Constraints on locational optimization problems. In: Proceedings of the 42nd IEEE Conference on Decision and Control, vol. 2, pp. 1741–1746. IEEE (2003)

    Google Scholar 

  15. Schwager, M., Bullo, F., Skelly, D., Rus, D.: A ladybug exploration strategy for distributed adaptive coverage control. In: IEEE International Conference on Robotics and Automation, ICRA 2008, pp. 2346–2353. IEEE (2008)

    Google Scholar 

  16. Schwager, M., Rus, D., Slotine, J.J.: Decentralized, adaptive coverage control for networked robots. Int. J. Robot. Res. 28(3), 357–375 (2009)

    Article  Google Scholar 

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Acknowledgments

This work was supported in part by ONR grant N00014-12-1-1000, and by a Clare Boothe Luce Fellowship. We are grateful for this financial support.

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Authors and Affiliations

  1. Boston University, Boston, MA, 02215, USA

    Alyssa Pierson

  2. Stanford University, Stanford, CA, 94305, USA

    Mac Schwager

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  1. Alyssa Pierson
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  2. Mac Schwager
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Correspondence to Alyssa Pierson .

Editor information

Editors and Affiliations

  1. Creative Informatics, The University of Tokyo, Tokyo, Japan

    Masayuki Inaba

  2. School of Electrical Engineering and Com, Queensland Univ of Technology, Brisbane, Queensland, Australia

    Peter Corke

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Pierson, A., Schwager, M. (2016). Adaptive Inter-Robot Trust for Robust Multi-Robot Sensor Coverage. In: Inaba, M., Corke, P. (eds) Robotics Research. Springer Tracts in Advanced Robotics, vol 114. Springer, Cham. https://doi.org/10.1007/978-3-319-28872-7_10

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  • DOI: https://doi.org/10.1007/978-3-319-28872-7_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-28870-3

  • Online ISBN: 978-3-319-28872-7

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