Abstract
NoStop is an open source simulator dedicated to distributed and cooperative mobile robotics systems. It has been designed as a framework to design and test multi–agent collaborative algorithms in terms of performance and robustness. The particular application scenario of a team of autonomous guards that coordinate to protect an area from asymmetric threat is considered. NoStop system is an integrated tool able to both evaluate the coordination protocol performance and to design the team of guards involved in the asymmetric threat protection. Moreover, NoStop is designed to validate robustness of coordination protocol through the use of a remote pilot that control the intruder motion to escape from the guards that monitor the area and accomplish its mission. The project core is a simulation server with a dynamic engine and a synchronization facility. Different coordination protocol can be designed and easily integrated in NoStop. The framework is fully integrated with the Robot Operating System (ROS) and it is completed by a control station where the remote pilot moves the intruder following the guards evolution in a 3D viewer.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
The entire code can be downloaded from https://github.com/SimoneNardi/nostop.
References
Blank, S.J.: Rethinking asymmetric threats. Technical report, DTIC Document (2003)
Sutton, D.J.: Maritime force protection operations analysis methodology development. In: International Maritime Protection Symposium, USA, pp. 12–14, December 2005
Kessel, R.T., Strode, C., Hollett, R.D.: Nonlethal weapons for port protection: scenarios and methodology. In: 5th European Symposium on Non-lethal Weapons (2009)
Quigley, M., Conley, K., Gerkey, B., Faust, J., Foote, T., Leibs, J., Wheeler, R., Ng, A.Y.: Ros: an open-source robot operating system. In: ICRA Workshop on Open Source Software, vol. 3, p. 5 (2009)
Marden, J.R.: Selecting efficient correlated equilibria through distributed learning. In: American Control Conference (ACC), pp. 4048–4053. IEEE (2015)
Goto, T., Hatanaka, T., Fujita, M.: Payoff-based inhomogeneous partially irrational play for potential game theoretic cooperative control: convergence analysis. In: American Control Conference (ACC), pp. 2380–2387. IEEE (2012)
Zhu, M., Martínez, S.: Distributed coverage games for energy-aware mobile sensor networks. SIAM J. Control Optim. 51(1), 1–27 (2013)
Nardi, S., Santina, C.D., Meucci, D., Pallottino, L.: Coordination of unmanned marine vehicles for asymmetric threats protection. In: OCEANS 2015-Genova, pp. 1–7. IEEE (2015)
Nardi, S., Fabbri, T., Caiti, A., Pallottino, L.: A game theoretic approach for antagonistic-task coordination of underwater autonomous robots in asymmetric threats scenarios. In: OCEANS 2016-Monterey. IEEE (2016)
Faralli, A., Niko, G., Nardi, S., Pallottino, L.: Indoor real-time localisation for multiple autonomous vehicles fusing vision, odometry and IMU data. In: Hodicky, J. (ed.) MESAS 2016. LNCS, vol. 9991, pp. 288–297. Springer, Heidelberg (2016)
Borowski, H.P., Marden, J.R., Shamma, J.S.: Learning efficient correlated equilibria. In: 2014 IEEE 53rd Annual Conference on Decision and Control (CDC), pp. 6836–6841. IEEE (2014)
Jason, R.M., Young, H.P., Pao, L.Y.: Achieving pareto optimality through distributed learning. SIAM J. Control Optim. 52(5), 2753–2770 (2014)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing AG
About this paper
Cite this paper
Nardi, S., Pallottino, L. (2016). NoStop: An Open Source Framework for Design and Test of Coordination Protocol for Asymmetric Threats Protection in Marine Environment. In: Hodicky, J. (eds) Modelling and Simulation for Autonomous Systems. MESAS 2016. Lecture Notes in Computer Science(), vol 9991. Springer, Cham. https://doi.org/10.1007/978-3-319-47605-6_14
Download citation
DOI: https://doi.org/10.1007/978-3-319-47605-6_14
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-47604-9
Online ISBN: 978-3-319-47605-6
eBook Packages: Computer ScienceComputer Science (R0)