nach oben

Erschienen in:

07.11.2018

Robust connectivity maintenance for fallible robots

verfasst von: Jacopo Panerati, Marco Minelli, Cinara Ghedini, Lucas Meyer, Marcel Kaufmann, Lorenzo Sabattini, Giovanni Beltrame

Erschienen in: Autonomous Robots | Ausgabe 3/2019

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config

KI-gestützte Suche

Aus

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.

Vorheriger Artikel Resilient distributed state estimation with mobile agents: overcoming Byzantine adversaries, communication losses, and intermittent measurements

Nächster Artikel Real-time distributed non-myopic task selection for heterogeneous robotic teams

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

Jetzt informieren

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 \(\varDelta \).

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

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

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

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

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

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].

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.MathSciNetCrossRefMATH

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

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.CrossRef

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.CrossRef

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.CrossRef

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.CrossRef

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

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.MathSciNetCrossRefMATH

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.CrossRef

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

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

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.CrossRef

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.MathSciNetCrossRef

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.MathSciNetCrossRef

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

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.MathSciNetCrossRefMATH

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.CrossRef

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

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

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.

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.CrossRef

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.CrossRef

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.CrossRef

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.CrossRef

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.CrossRef

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.CrossRef

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.CrossRef

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.MathSciNetCrossRefMATH

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.

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.CrossRef

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.CrossRef

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.CrossRefMATH

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.MathSciNetCrossRefMATH

Titel: Robust connectivity maintenance for fallible robots
verfasst von: Jacopo Panerati
Marco Minelli
Cinara Ghedini
Lucas Meyer
Marcel Kaufmann
Lorenzo Sabattini
Giovanni Beltrame
Publikationsdatum: 07.11.2018
Verlag: Springer US
Erschienen in: Autonomous Robots / Ausgabe 3/2019
Print ISSN: 0929-5593
Elektronische ISSN: 1573-7527
DOI: https://doi.org/10.1007/s10514-018-9812-8

Neuer Inhalt

Bildnachweise

Smart-Manufacturing Dashboard Banner/© AdobeStock_583269095, VDI-Icon, Profil Icon, inhalt2, Springer Professional Modul/© Springer Fachmedien Wiesbaden GmbH, Nachhaltigkeitsaward Key Visual/© Cometis AG/Global ESG Monitor | Daniel Rupp | Generiert mit KI, Search Icon, Banner Hanser, Leads Kundenakquise/© Andrey Popov / stock.adobe.com, Schiffschraube/© Angelika Bentin | stock.adobe.com, Rudergelenkwelle/© Weicon GmbH & Co. KG, Digitalisierung im Marketing/© Fotolia/alphaspirit, Zeitschrift Wissensmanagement Cover, PatentFit-Logo/© Springer Fachmedien Wiesbaden GmbH, Sustainibility Finance/© Robert Kneschke / stock.adobe.com / Springer Fachmedien Wiesbaden GmbH, Zukunftswerkstatt Sales Excellence 2024/© AndreyPopov / Getty Images / iStock, 2023_Antrieb/© supervisuell

Springer Professional

Abstract

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Technik"

Weitere Artikel der Ausgabe 3/2019

Coordination of multiple AGVs: a quadratic optimization method

Automatic semantic maps generation from lexical annotations

Resilient distributed state estimation with mobile agents: overcoming Byzantine adversaries, communication losses, and intermittent measurements

Multi-robot grasp planning for sequential assembly operations

Real-time distributed non-myopic task selection for heterogeneous robotic teams

Windowed multiscan optimization using weighted least squares for improving localization accuracy of mobile robots

Neuer Inhalt

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.