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Robust connectivity maintenance for fallible robots

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Abstract

Multi-robot systems are promising tools for many hazardous real-world problems. In particular, the practical application of swarm robotics was identified as one of the grand challenges of the next decade. As swarms enter the real world, they have to deal with the inevitable problems of hardware, software, and communication failure, especially for long-term deployments. Communication is a key element for effective collaboration, and the ability of robots to communicate is expressed by the swarm’s connectivity. In this paper, we analyze a set of techniques to assess, control, and enforce connectivity in the context of fallible robots. Past research has addressed the issue of connectivity but, for the most part, without making system reliability a constitutional part of the model. We introduce a controller for connectivity maintenance in the presence of faults and discuss the optimization of its parameters and performance. We validate our approach in simulation and via physical robot experiments.

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Notes

  1. This definition of the edge-weights introduces a discontinuity in the control action that can be avoided introducing a smooth bump function (Do 2008). However, from an implementation viewpoint, the effect of the discontinuity can be made negligible by choosing a sufficiently small threshold \(\varDelta \).

  2. https://www.k-team.com/mobile-robotics-products/khepera-iv.

  3. https://github.com/MISTLab/Buzz.

  4. https://github.com/MISTLab/BuzzKH4.

  5. http://optitrack.com/products/prime-13/specs.html.

  6. https://github.com/MISTLab/blabbermouth.

  7. To do so, we evaluated all the combinations of gains using the following values: [0.01, 0.25, 0.5, 0.75, 1., 1.5, 2.0].

References

  • Ajorlou, A., Momeni, A., & Aghdam, A. G. (2010). A class of bounded distributed control strategies for connectivity preservation in multi-agent systems. IEEE Transactions on Automatic Control, 55, 2828–2833.

    Article  MathSciNet  MATH  Google Scholar 

  • Albert, R., Jeong, H., & Barabasi, A. L. (2000). Error and attack tolerance of complex networks. Nature, 406(6794), 378–382.

    Article  Google Scholar 

  • Avizienis, A., Laprie, J. C., Randell, B., & Landwehr, C. (2004). Basic concepts and taxonomy of dependable and secure computing. IEEE Transactions on Dependable and Secure Computing, 1(1), 11–33. https://doi.org/10.1109/TDSC.2004.2.

    Article  Google Scholar 

  • Bertrand, A., & Moonen, M. (2013). Distributed computation of the fiedler vector with application to topology inference in ad hoc networks. Signal Processing, 93(5), 1106–1117. https://doi.org/10.1016/j.sigpro.2012.12.002.

    Article  Google Scholar 

  • Biscani, F., Izzo, D., & Märtens, M. (2017). esa/pagmo2: pagmo 2.6. https://doi.org/10.5281/zenodo.1054110.

  • Brambilla, M., Ferrante, E., Birattari, M., & Dorigo, M. (2013). Swarm robotics: A review from the swarm engineering perspective. Swarm Intelligence, 7(1), 1–41. https://doi.org/10.1007/s11721-012-0075-2.

    Article  Google Scholar 

  • Cao, Y., & Ren, W. (2010). Distributed coordinated tracking via a variable structure approach—part I: Consensus tracking. part II: Swarm tracking. In Proceedings of the American Control Conference, (pp. 4744–4755).

  • Couceiro, M. S., Figueiredo, C. M., Rocha, R. P., & Ferreira, N. M. (2014). Darwinian swarm exploration under communication constraints: Initial deployment and fault-tolerance assessment. Robotics and Autonomous Systems, 62(4), 528–544. https://doi.org/10.1016/j.robot.2013.12.009.

    Article  Google Scholar 

  • Cvetkovic, D., & Rowlinson, P. (2004). Spectral graph theory. In L. W. Beineke, R. J. Wilson, & P. J. Cameron (Eds.), Topics in algebraic graph theory (pp. 88–112). Cambridge University Press.

  • Deb, K., & Deb, K. (2014). Multi-objective Optimization (pp. 403–449). Boston: Springer. https://doi.org/10.1007/978-1-4614-6940-7_15.

    MATH  Google Scholar 

  • Di Lorenzo, P., & Barbarossa, S. (2014). Distributed estimation and control of algebraic connectivity over random graphs. IEEE Transactions on Signal Processing, 62(21), 5615–5628. https://doi.org/10.1109/TSP.2014.2355778.

    Article  MathSciNet  MATH  Google Scholar 

  • Do, K. D. (2008). Formation tracking control of unicycle-type mobile robots with limited sensing ranges. IEEE Transactions on Control Systems Technology, 16, 527–538.

    Article  Google Scholar 

  • Elsayed, E. A. (2012). Reliability engineering (2nd ed.). Hoboken: Wiley Publishing.

    MATH  Google Scholar 

  • Fiedler, M. (1973). Algebraic connectivity of graphs. Czechoslovak Mathematical Journal, 23(2), 298–305.

    MathSciNet  MATH  Google Scholar 

  • Gasparri, A., Sabattini, L., & Ulivi, G. (2017). Bounded control law for global connectivity maintenance in cooperative multi-robot systems. IEEE Transactions on Robotics, 33(3), 700–717. https://doi.org/10.1109/TRO.2017.2664883.

    Article  Google Scholar 

  • Ghedini, C., & Ribeiro, C. H. C. (2011). Rethinking failure and attack tolerance assessment in complex networks. Physica A: Statistical Mechanics and its Applications, 390(23–24), 4684–4691.

    Article  MathSciNet  Google Scholar 

  • Ghedini, C., Secchi, C., Ribeiro, C.H.C., & Sabattini, L. (2015). Improving robustness in multi-robot networks. In: Proceedings of the IFAC Symposium on Robot Control (SYROCO), Salvador, Brazil.

  • Ghedini, C., Ribeiro, C.H.C., & Sabattini, L. (2016). A decentralized control strategy for resilient connectivity maintenance in multi-robot systems subject to failures. In Proceedings of the International Symposium on Distributed Autonomous Robotic Systems (DARS), London, UK.

  • Ghedini, C., Ribeiro, C., & Sabattini, L. (2017). Toward fault-tolerant multi-robot networks. Networks, 70(4), 388–400. https://doi.org/10.1002/net.21784.

    Article  MathSciNet  Google Scholar 

  • Godsil, C., & Royle, G. (2001). Algebraic graph theory. Berlin: Springer.

    Book  MATH  Google Scholar 

  • Gupta, S., Ansari, A., Feng, S., & Mahlke, S. (2009). Adaptive online testing for efficient hard fault detection. In: 2009 IEEE International Conference on Computer Design, IEEE, (pp. 343–349). https://doi.org/10.1109/ICCD.2009.5413132.

  • Gutierrez, A., Campo, A., Dorigo, M., Donate, J., Monasterio-Huelin, F., & Magdalena, L. (2009). Open e-puck range and bearing miniaturized board for local communication in swarm robotics. In 2009 IEEE International Conference on Robotics and Automation, (pp. 3111–3116), https://doi.org/10.1109/ROBOT.2009.5152456.

  • He, Z., Liu, S., & Zhan, M. (2013). Dynamical robustness analysis of weighted complex networks. Physica A: Statistical Mechanics and its Applications, 392(18), 4181–4191.

    Article  MathSciNet  MATH  Google Scholar 

  • Hsieh, M. A., Cowley, A., Kumar, V., & Talyor, C. J. (2008). Maintaining network connectivity and performance in robot teams. Journal of Field Robotics, 25(1), 111–131.

    Article  Google Scholar 

  • Hutter, F., Hoos, H. H., & Stützle, T. (2007). Automatic algorithm configuration based on local search. Aaai, 7, 1152–1157.

    Google Scholar 

  • Ji, M., & Egerstedt, M. (2007). Distributed coordination control of multiagent systems while preserving connectedness. IEEE Transactions on Robotics, 23, 693–703.

    Article  Google Scholar 

  • Kantor, G., Singh, S., Peterson, R., Rus, D., Das, A., Kumar, V., et al. (2006). Distributed search and rescue with robot and sensor teams (pp. 529–538). Berlin: Springer. https://doi.org/10.1007/10991459_51.

    Google Scholar 

  • Karnik, T., & Hazucha, P. (2004). Characterization of soft errors caused by single event upsets in cmos processes. IEEE Transactions on Dependable and Secure Computing, 1(2), 128–143. https://doi.org/10.1109/TDSC.2004.14.

    Article  Google Scholar 

  • Krupke, D., Ernestus, M., Hemmer, M., & Fekete, S.P. (2015). Distributed cohesive control for robot swarms: Maintaining good connectivity in the presence of exterior forces. In 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), (pp. 413–420). https://doi.org/10.1109/IROS.2015.7353406

  • Manzano, M., Calle, E., Torres-Padrosa, V., Segovia, J., & Harle, D. (2013). Endurance: A new robustness measure for complex networks under multiple failure scenarios. Computer Networks, 57(17), 3641–3653.

    Article  Google Scholar 

  • Minelli, M., Kaufmann, M., Panerati, J., Ghedini, C., Beltrame, G., & Sabattini, L. (2018). Stop, think, and roll: Online gain optimization for resilient multi-robot topologies. In Proceedings of the International Symposium on Distributed Autonomous Robotic Systems (DARS), Boulder, CO.

  • Mosteo, A.R., Montano, L., & Lagoudakis, M.G. (2008). Multi-robot routing under limited communication range. In 2008 IEEE International Conference on Robotics and Automation, (pp. 1531–1536). https://doi.org/10.1109/ROBOT.2008.4543419

  • Notarstefano, G., Savla, K., Bullo, F., & Jadbabaie, A. (2006). Maintaining limited–range connectivity among second–order agents. In Proceedings of the American Control Conference, (pp. 2134–2129).

  • Panerati, J., Abdi, S., & Beltrame, G. (2014). Balancing system availability and lifetime with dynamic hidden markov models. In 2014 NASA/ESA Conference on Adaptive Hardware and Systems (AHS), (pp. 240–247). https://doi.org/10.1109/AHS.2014.6880183.

  • Panerati, J., Gianoli, L., Pinciroli, C., Shabah, A., Nicolescu, G., & Beltrame, G. (2018). From swarms to stars: Task coverage in robot swarms with connectivity constraints. In 2018 IEEE International Conference on Robotics and Automation (ICRA).

  • Pei, Y., Mutka, M.W., & Xi, N. (2010). Coordinated multi-robot real-time exploration with connectivity and bandwidth awareness. In 2010 IEEE International Conference on Robotics and Automation, (pp. 5460–5465). https://doi.org/10.1109/ROBOT.2010.5509803

  • Pinciroli, C., & Beltrame, G. (2016). Swarm-oriented programming of distributed robot networks. Computer, 49(12), 32–41.

    Article  Google Scholar 

  • Pinciroli, C., Trianni, V., O’Grady, R., Pini, G., Brutschy, A., Brambilla, M., et al. (2012). Argos: A modular, parallel, multi-engine simulator for multi-robot systems. Swarm Intelligence, 6(4), 271–295. https://doi.org/10.1007/s11721-012-0072-5.

    Article  Google Scholar 

  • Pinciroli, C., Lee-Brown, A., & Beltrame, G. (2016). A tuple space for data sharing in robot swarms. In Proceedings of the 9th EAI International Conference on Bio-inspired Information and Communications Technologies (Formerly BIONETICS), ICST (Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering), BICT’15, ICST, Brussels, (pp. 287–294). https://doi.org/10.4108/eai.3-12-2015.2262503

  • Poonawala, H.A., & Spong, M.W. (2015). Decentralized estimation of the algebraic connectivity for strongly connected networks. In American Control Conference (ACC), IEEE, (pp. 4068–4073).

  • Rathnam, & Birk, A. (2011). Distributed communicative exploration under underwater communication constraints. In 2011 IEEE International Symposium on Safety, Security, and Rescue Robotics, (pp. 339–344). https://doi.org/10.1109/SSRR.2011.6106767

  • Roberts, J.F., Stirling, T.S., Zufferey, J.C., & Floreano, D. (2009). 2.5d infrared range and bearing system for collective robotics. In 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems, (pp. 3659–3664). https://doi.org/10.1109/IROS.2009.5354263

  • Robuffo Giordano, P., Franchi, A., Secchi, C., & Bülthoff, H. H. (2013). A passivity-based decentralized strategy for generalized connectivity maintenance. The International Journal of Robotics Research, 32(3), 299–323.

    Article  Google Scholar 

  • Sabattini, L., Chopra, N., & Secchi, C. (2013a). Decentralized connectivity maintenance for cooperative control of mobile robotic systems. The International Journal of Robotics Research, 32(12), 1411–1423. https://doi.org/10.1177/0278364913499085.

    Article  Google Scholar 

  • Sabattini, L., Secchi, C., Chopra, N., & Gasparri, A. (2013b). Distributed control of multi-robot systems with global connectivity maintenance. IEEE Transactions on Robotics, 29(5), 1326–1332.

    Article  Google Scholar 

  • Sahai, T., Speranzon, A., & Banaszuk, A. (2012). Hearing the clusters of a graph: A distributed algorithm. Automatica, 48(1), 15–24. https://doi.org/10.1016/j.automatica.2011.09.019.

    Article  MathSciNet  MATH  Google Scholar 

  • Şahin, E., Girgin, S., Bayindir, L., & Turgut, A. E. (2008). Swarm robotics (pp. 87–100). Berlin: Springer. https://doi.org/10.1007/978-3-540-74089-6_3.

    Google Scholar 

  • Støy, K. (2001). Using situated communication in distributed autonomous mobile robotics. In Proceedings of the Seventh Scandinavian Conference on Artificial Intelligence, SCAI ’01, IOS Press, Amsterdam, (pp. 44–52). URL http://dl.acm.org/citation.cfm?id=645855.669785

  • Tardioli, D., Mosteo, A., Riazuelo, L., Villarroel, J., & Montano, L. (2010). Enforcing network connectivity in robot team missions. The International Journal of Robotics Research, 29(4), 460–480. https://doi.org/10.1177/0278364909358274.

    Article  Google Scholar 

  • Vasisht, D., Kumar, S., & Katabi, D. (2016). Decimeter-level localization with a single wifi access point. In 13th USENIX Symposium on Networked Systems Design and Implementation (NSDI 16), USENIX Association, Santa Clara, (pp. 165–178). URL https://www.usenix.org/conference/nsdi16/technical-sessions/presentation/vasisht

  • Wasserman, S., Faust, K., & Iacobucci, D. (1994). Social network analysis : Methods and applications (structural analysis in the social sciences). Cambridge: Cambridge University Press.

    Book  Google Scholar 

  • Xiao, L., Boyd, S., & Kim, S. J. (2007). Distributed average consensus with least-mean-square deviation. Journal of Parallel and Distributed Computing, 67(1), 33–46. https://doi.org/10.1016/j.jpdc.2006.08.010.

    Article  MATH  Google Scholar 

  • Yang, P., Freeman, R. A., Gordon, G. J., Lynch, K. M., Srinivasa, S. S., & Sukthankar, R. (2010). Decentralized estimation and control of graph connectivity for mobile sensor networks. Automatica, 46(2), 390–396.

    Article  MathSciNet  MATH  Google Scholar 

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Acknowledgements

The authors would like to thank Québec’s Ministère des Relations Internationales et de la Francophonie (MRIF) and Italy’s Ministry of Foreign Affairs and International Cooperation (MAECI) for supporting SCMQI’s project QU17MO04 “Maintenance and Control of Distributed Robot and Sensor Network”.

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Authors and Affiliations

  1. Department of Computer and Software Engineering, Polytechnique Montréal, Montreal, Canada

    Jacopo Panerati, Lucas Meyer, Marcel Kaufmann & Giovanni Beltrame

  2. Department of Science and Methods of Engineering, Università degli Studi di Modena e Reggio Emilia, Reggio Emilia, Italy

    Marco Minelli & Lorenzo Sabattini

  3. Departamento de Computação Científica, Instituto Tecnológico de Aeronáutica, São José dos Campos, Brazil

    Cinara Ghedini

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  1. Jacopo Panerati
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Correspondence to Jacopo Panerati.

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This is one of the several papers published in Autonomous Robots comprising the Special Issue on Foundations of Resilience for Networked Robotic Systems.

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Panerati, J., Minelli, M., Ghedini, C. et al. Robust connectivity maintenance for fallible robots. Auton Robot 43, 769–787 (2019). https://doi.org/10.1007/s10514-018-9812-8

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