Abstract
Efficient and autonomous execution of large-scale missions using a group of robots implies the use of an advanced control system, usually consisting of multiple subsystems arranged in a hierarchy. For the purpose of unification of interaction of separate subsystems, an event-based cooperative control framework for robot teams is developed. In the paper, we demonstrate how this framework can be used in solving challenging problems in robotics: path-following problem, real-time path-planning problem, group routing problem, and action-planning problem. A novel approach to formalization and analysis of logic discrete event systems, which are the main component of the framework, based on logic calculus and automatic theorem proving is also briefly described.
The event-triggered control framework has been mostly designed under support of the RFBR (Projects No. 20-07-00397 and No. 19-08-00746). Results of Sects. 4, 7 have been obtained under support of the Russian Science Foundation (Project No. 16-11-00053).
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Bychkov, I., Davydov, A., Kenzin, M., Maksimkin, N., Nagul, N., Ul’yanov, S.: Hierarchical control system design problems for multiple autonomous underwater vehicles. In: 2019 International Siberian Conference on Control and Communications (SIBCON), pp. 1–6 (2019). https://doi.org/10.1109/SIBCON.2019.8729592
Bychkov, I., Davydov, A., Nagul, N., Ul’yanov, S.: Hybrid control approach to multi-AUV system in a surveillance mission. Inf. Technol. Ind. 6(1), 20–26 (2018)
Caceres-Cruz, J., Arias, P., Guimarans, D., Riera, D., Juan, A.A.: Rich vehicle routing problem: survey. ACM Comput. Surv. 47(2) (2014). https://doi.org/10.1145/2666003
Cassandras, C.G., Lafortune, S.: Introduction to Discrete Event Systems. Springer, Heidelberg (2008). https://doi.org/10.1007/978-0-387-68612-7
Chu, X., Peng, Z., Wen, G., Rahmani, A.: Distributed formation tracking of multi-robot systems with nonholonomic constraint via event-triggered approach. Neurocomputing 275, 121–131 (2018). https://doi.org/10.1016/j.neucom.2017.05.007
Cissé, M., Yalçındağ, S., Kergosien, Y., Şahin, E., Lenté, C., Matta, A.: Or problems related to home health care: a review of relevant routing and scheduling problems. Oper. Res. Health Care 13–14, 1–22 (2017). https://doi.org/10.1016/j.orhc.2017.06.001
Dai, X., Jiang, L., Zhao, Y.: Cooperative exploration based on supervisory control of multi-robot systems. Appl. Intell. 45(1), 18–29 (2016). https://doi.org/10.1007/s10489-015-0741-3
Davies, T., Jnifene, A., Davies, T.: Path planning and trajectory control of collaborative mobile robots using hybrid control architecture. J. Syst. Cybern. Inform. 6 (2013)
Dubins, E.L.: On curves of minimal length with a constraint on average curvature, and with prescribed initial and terminal positions and tangents. Am. J. Math. (1957)
Dunbabin, M., Marques, L.: Robots for environmental monitoring: significant advancements and applications. IEEE Robot. Autom. Mag. 19(1), 24–39 (2012). https://doi.org/10.1109/MRA.2011.2181683
Hartl, R., Hasle, G., Janssens, G.: Special issue on rich vehicle routing problems. CEJOR 14, 103–104 (2006). https://doi.org/10.1007/s10100-006-0162-9
Hernández, J.D., Vidal, E., Moll, M., Palomeras, N., Carreras, M., Kavraki, L.E.: Online motion planning for unexplored underwater environments using autonomous underwater vehicles. J. Field Robot. 36(2), 370–396 (2019). https://doi.org/10.1002/rob.21827
Ju, C., Son, H.I.: Modeling and control of heterogeneous agricultural field robots based on Ramadge–Wonham theory. IEEE Robot. Autom. Lett. 5(1), 48–55 (2020)
Kenzin, M., Bychkov, I., Maksimkin, N.: Task allocation and path planning for network of autonomous underwater vehicle. Int. J. Comput. Netw. Commun. 10(2), 33–42 (2018). https://doi.org/10.5121/ijcnc.2018.10204
Kozlov, R.I., Kozlova, O.R.: Investigation of stability of nonlinear continuous-discrete models of economic dynamics using vector Iyapunov function. I. J. Comput. Syst. Sci. Int. 48(2), 262–271 (2009). https://doi.org/10.1134/S1064230709020105
Koç, Ç., Bektaş, T., Jabali, O., Laporte, G.: Thirty years of heterogeneous vehicle routing. Eur. J. Oper. Res. 249(1), 1–21 (2016). https://doi.org/10.1016/j.ejor.2015.07.020
Lapierre, L., Soetanto, D.: Nonlinear path-following control of an AUV. Ocean Eng. 34(11), 1734–1744 (2007). https://doi.org/10.1016/j.oceaneng.2006.10.019
Laporte, G., Røpke, S., Vidal, T.: Heuristics for the Vehicle Routing Problem, 2 edn., pp. 87–116. Society for Industrial and Applied Mathematics (2014)
Larionov, A., Davydov, A., Cherkashin, E.: The calculus of positively constructed formulas, its features, strategies and implementation. In: International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO), Opatija 2013, pp. 1023–1028 (2013)
Li, D., Wang, P., Du, L.: Path planning technologies for autonomous underwater vehicles-a review. IEEE Access 7, 9745–9768 (2019)
Liu, X., Ge, S.S., Goh, C., Li, Y.: Event-triggered coordination for formation tracking control in constrained space with limited communication. IEEE Trans. Cybern. 49(3), 1000–1011 (2019)
Manyam, S.G., Casbeer, D.W., Moll, A.V., Fuchs, Z.: Shortest Dubins path to a circle. arXiv, Optimization and Control (2018)
Medeiros, A.A.D.: A survey of control architectures for autonomous mobile robots. J. Braz. Comput. Soc. 4 (1998)
Metoui, F., Boussaid, B., Abdelkrim, M.N.: Path planning for a multi-robot system with decentralized control architecture. In: Ghommam, J., Derbel, N., Zhu, Q. (eds.) New Trends in Robot Control. SSDC, vol. 270, pp. 229–259. Springer, Singapore (2020). https://doi.org/10.1007/978-981-15-1819-5_12
Nair, R.R., Behera, L., Kumar, S.: Event-triggered finite-time integral sliding mode controller for consensus-based formation of multirobot systems with disturbances. IEEE Trans. Control Syst. Technol. 27(1), 39–47 (2019)
Panda, M., Das, B., Subudhi, B., Pati, B.B.: A comprehensive review of path planning algorithms for autonomous underwater vehicles. Int. J. Autom. Comput. 17(3), 321–352 (2020). https://doi.org/10.1007/s11633-019-1204-9
Ramadge, P.J., Wonham, W.M.: Supervisory control of a class of discrete event processes. SIAM J. Control Optim. 25(1), 206–230 (1987)
Ren, W., Sorensen, N.: Distributed coordination architecture for multi-robot formation control. Robot. Autonom. Syst. 56(4), 324–333 (2008). https://doi.org/10.1016/j.robot.2007.08.005
Seatzu, C., Silva, M., van Schuppen, J.H. (eds.): Control of Discrete-Event Systems. Springer, London (2013). https://doi.org/10.1007/978-1-4471-4276-8
Shepard, J.T., Kitts, C.A.: A multirobot control architecture for collaborative missions comprised of tightly coupled, interconnected tasks. IEEE Syst. J. 12(2), 1435–1446 (2018). https://doi.org/10.1109/JSYST.2016.2590430
Ulyanov, S., Maksimkin, N.: Formation path-following control of multi-AUV systems with adaptation of reference speed. Math. Eng. Sci. Aerosp. (MESA) 10(3), 487–500 (2019)
Vassilyev, S.N.: Machine synthesis of mathematical theorems. J. Logic Program. 9(2–3), 235–266 (1990). https://doi.org/10.1016/0743-1066(90)90042-4
Vassilyev, S., Ulyanov, S., Maksimkin, N.: A VLF-based technique in applications to digital control of nonlinear hybrid multirate systems. In: AIP Conference Proceedings, pp. 020170(1)–020170(10) (2017). https://doi.org/10.1063/1.4972762
Wonham, W.M., Cai, K.: Supervisory Control of Discrete-Event Systems. Springer, Heidelberg (2019). https://doi.org/10.1007/978-3-319-77452-7
Yan, Z., Li, J., Zhang, G., Wu, Y.: A real-time reaction obstacle avoidance algorithm for autonomous underwater vehicles in unknown environments. Sensors 18(2) (2018). https://doi.org/10.3390/s18020438
Yao, X., Wang, X., Wang, F., Zhang, L.: Path following based on waypoints and real-time obstacle avoidance control of an autonomous underwater vehicle. Sensors 20(3) (2020). https://doi.org/10.3390/s20030795
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Bychkov, I., Ul’yanov, S., Nagul, N., Davydov, A., Kenzin, M., Maksimkin, N. (2020). Event-Based Cooperative Control Framework for Robot Teams. In: Qian, J., Liu, H., Cao, J., Zhou, D. (eds) Robotics and Rehabilitation Intelligence. ICRRI 2020. Communications in Computer and Information Science, vol 1336. Springer, Singapore. https://doi.org/10.1007/978-981-33-4932-2_9
Download citation
DOI: https://doi.org/10.1007/978-981-33-4932-2_9
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-33-4931-5
Online ISBN: 978-981-33-4932-2
eBook Packages: Computer ScienceComputer Science (R0)