Abstract
Efficient networking of many-robot systems is considered one of the grand challenges of robotics. In this article, we address the problem of achieving resilient, dynamic interconnection topologies in multi-robot systems. In scenarios in which the overall network topology is constantly changing, we aim at avoiding the onset of single points of failure, particularly situations in which the failure of a single robot causes the loss of connectivity for the overall network. We propose a method based on the combination of multiple control objectives and we introduce an online distributed optimization strategy that computes the optimal choice of control parameters for each robot. This ensures that the connectivity of the multi-robot system is not only preserved but also made more resilient to failures, as the network topology evolves. We provide simulation results, as well as experiments with real robots to validate theoretical findings and demonstrate the portability to robotic hardware.
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Notes
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Pathological situations may exist in which (10) is not well defined, namely when \(p_i = x_\beta ^i\). However, this corresponds to the case where the i-th robot is exactly in the barycenter of its weakly connected 2-hop neighbors: in practice, this never happens when a robot detects itself as vulnerable.
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References
Avriel, M.: Nonlinear Programming: Analysis and Methods. Courier Corporation (2003)
Brambilla, M., Ferrante, E., Birattari, M., Dorigo, M.: Swarm robotics: a review from the swarm engineering perspective. Swarm Intell. 7(1), 1–41 (2013)
Gasparri, A., Sabattini, L., Ulivi, G.: Bounded control law for global connectivity maintenance in cooperative multi-robot systems. IEEE Trans. Robot. 33(3), 700–717 (2017)
Ghedini, C., Ribeiro, C.H.C., Sabattini, L.: Toward efficient adaptive ad-hoc multi-robot network topologies. Ad Hoc Netw. 74, 57–70 (2018)
Ghedini, C., Secchi, C., Ribeiro, C.H.C., Sabattini, L.: Improving robustness in multi-robot networks. In: Proceedings of the IFAC Symposium on Robot Control (SYROCO), Salvador, Brazil, Aug 2015
Ghedini, C., Ribeiro, C., Sabattini, L.: Toward fault-tolerant multi-robot networks. Networks 70(4), 388–400 (2017). https://onlinelibrary.wiley.com/doi/abs/10.1002/net.21784
Godsil, C., Royle, G.: Algebraic Graph Theory. Springer (2001)
Ji, M., Egerstedt, M.: Distributed coordination control of multiagent systems while preserving connectedness. IEEE Trans. Robot. (2007)
Koschützki, D., Lehmann, K.A., Peeters, L., Richter, S., Tenfelde-Podehl, D., Zlotowski, O.: Centrality indices. Network Analysis, pp. 16–61. Springer (2005)
Panerati, J., Minelli, M., Ghedini, C., Meyer, L., Kaufmann, M., Beltrame, G., Sabattini, L.: Robust connectivity maintenance for fallible robots. Autonomous Robots (2018). https://doi.org/10.1007/s10514-018-9812-8
Panerati, J., Beltrame, G.: A comparative evaluation of multi-objective exploration algorithms for high-level design. ACM Trans. Des. Autom. Electron. Syst. 19(2), 15:1–15:22 (2014)
Pinciroli, C., Beltrame, G.: Swarm-oriented programming of distributed robot networks. Computer 49(12), 32–41 (2016)
Pinciroli, C., Lee-Brown, A., Beltrame, G.: 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), pp. 287–294, BICT’15, ICST (Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering), ICST, Brussels, Belgium (2016). https://doi.org/10.4108/eai.3-12-2015.2262503
Pinciroli, C., Trianni, V., O’Grady, R., Pini, G., Brutschy, A., Brambilla, M., Mathews, N., Ferrante, E., Di Caro, G., Ducatelle, F., Birattari, M., Gambardella, L.M., Dorigo, M.: Argos: a modular, parallel, multi-engine simulator for multi-robot systems. Swarm Intell. 6(4), 271–295 (2012). https://doi.org/10.1007/s11721-012-0072-5
Poonawala, H.A., Spong, M.W.: Decentralized estimation of the algebraic connectivity for strongly connected networks. In: American Control Conference (ACC), pp. 4068–4073. IEEE (2015)
Robuffo Giordano, P., Franchi, A., Secchi, C., Bülthoff, H.H.: A passivity-based decentralized strategy for generalized connectivity maintenance. Int. J. Robot. Res. 32(3), 299–323 (2013)
Sabattini, L., Chopra, N., Secchi, C.: Decentralized connectivity maintenance for cooperative control of mobile robotic systems. Int. J. Robot. Res. (SAGE) 32(12), 1411–1423 (2013)
Sabattini, L., Secchi, C., Chopra, N., Gasparri, A.: Distributed control of multi-robot systems with global connectivity maintenance. IEEE Trans. Robot. 29(5), 1326–1332 (2013)
Wasserman, S., Faust, K., Iacobucci, D.: Social Network Analysis : Methods and Applications (Structural Analysis in the Social Sciences). Cambridge University Press (1994)
Yang, G.Z., Bellingham, J., Dupont, P.E., Fischer, P., Floridi, L., Full, R., Jacobstein, N., Kumar, V., McNutt, M., Merrifield, R., et al.: The grand challenges of science robotics. Sci. Robot. 3(14), eaar7650 (2018)
Yang, P., Freeman, R.A., Gordon, G.J., Lynch, K.M., Srinivasa, S.S., Sukthankar, R.: Decentralized estimation and control of graph connectivity for mobile sensor networks. Automatica 46(2), 390–396 (2010)
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Minelli, M., Kaufmann, M., Panerati, J., Ghedini, C., Beltrame, G., Sabattini, L. (2019). Stop, Think, and Roll: Online Gain Optimization for Resilient Multi-robot Topologies. In: Correll, N., Schwager, M., Otte, M. (eds) Distributed Autonomous Robotic Systems. Springer Proceedings in Advanced Robotics, vol 9. Springer, Cham. https://doi.org/10.1007/978-3-030-05816-6_25
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