Abstract
Surveillance systems based on wireless sensor network technology have been shown to successfully detect, classify and track evaders over a large area. State information collected via the sensor network also enables these systems to actuate mobile agents so as to achieve surveillance goals, such as target capture and asset protection. But satisfying these goals is complicated by the fact that the track information in a sensor network is routed to mobile agents through multihop wireless communication links and is thus subject to message delays and losses. Stabilization must also be considered in designing pursuer strategies so as to deal with state corruption as well as suboptimal evader strategies.
In this article, we formulate optimal pursuit control strategies in the presence of network effects, assuming that target track information has been established locally in the sensor network. We adapt ideas from the theory of differential games to networked games—including ones involving nonperiodic track updates, message losses and message delays—to derive optimal strategies, bounds on the information requirements, and scaling properties of these bounds. We show the inherent stabilization features of our pursuit strategies, both in terms of implementation as well as the strategies themselves.
- Arora, A., Dutta, P., Bapat, S., Kulathumani, V., Zhang, H., Naik, V., Mittal, V., Cao, H., Demirbas, M., Gouda, M., Choi, Y., Herman, T., Kulkarni, S., Arumugam, U., Nesterenko, M., Vora, A., and Miyashita, M. 2004. A line in the sand: a wireless sensor network for target detection, classification, tracking. Comput. Netw. J. 46, 5, 605--634. Google Scholar
Digital Library
- Arora, A., Ertin, E., R. Ramnath, M. N., and Leal, W. 2006. Kansei: a high-fidelity sensing testbed. IEEE Internet Comput., 18--31. Google Scholar
Digital Library
- Arora, A., Ramnath, R., Ertin, E., Sinha, P., Bapat, S., Naik, V., Kulathumani, V., Zhang, H., Cao, H., Sridhara, M., Kumar, S., Seddon, N., Anderson, C., Herman, T., Trivedi, N., Zhang, C., Gouda, M., Choi, Y. R., Nesterenko, M., Shah, R., Kulkarni, S., Aramugam, M., Wang, L., Culler, D., Dutta, P., Sharp, C., Tolle, G., Grimmer, M., Ferriera, B., and Parker, K. 2005. Exscal: elements of an extreme scale wireless sensor network. In Proceedings of the 11th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA). IEEE Computer Society, Los Alamitos, CA. Google Scholar
Digital Library
- Basar, T. and Olsder, G. J. 1999. Dynamic Noncooperative Game Theory. SIAM.Google Scholar
- Cao, H., Ertin, E., Krishnan, V., Sridharan, M., and Arora, A. 2006. Differential games in large scale sensor actuator networks. In Proceedings of the 5th Symposium on Information Processing in Sensor Networks (IPSN). IEEE Computer Society, Los Alamitos, CA. 77--84. Google Scholar
Digital Library
- Chen, P. and Sastry, S. 2006. Pursuit controller performance guarantees for a lifeline pursuit-evasion game over a wireless sensor network. In Proceedings of the 45th IEEE Conference on Decision and Control. IEEE Computer Society, Los Alamitos, CA.Google Scholar
- Isaacs, R. 1975. Differential Games. Kruger Publishing Company, Huntington, NY.Google Scholar
- Kulathumani, V., Arora, A., Demirbas, M., and Sridharan, M. 2007. Trail: a distance sensitive network protocol for distributed object tracking. In Proceedings of European Conference on Wireless Sensor Networks (EWSN). Google Scholar
Digital Library
- Nash, J. 1951. Noncooperative games. Annals Math. 54, 286--295.Google Scholar
Cross Ref
- Oh, S., Russell, S., and Sastry, S. 2004. Markov chain monte carlo data association for general multiple-target tracking problems. In Proceedings of the IEEE International Conference on Decision and Control.Google Scholar
- Schenato, L., Oh, S., and Sastry, S. 2005. Swarm coordination for pursuit evasion games using sensor networks. In Proceedings of the International Conference on Robotics and Automation.Google Scholar
Index Terms
MiniMax equilibrium of networked differential games
Recommendations
Convergence of non-autonomous discrete-time Hopfield model with delays
This paper is concerned with boundedness, convergence of solution of a class of non-autonomous discrete-time delayed Hopfield neural network model. Using the inequality technique, we obtain some sufficient conditions ensuring the boundedness of ...
Global exponential stability and global attractivity of impulsive Hopfield neural networks with time delays
In this paper, by means of constructing the extended impulsive delayed Halanay inequality and by Lyapunov functional methods, we analyze the global exponential stability and global attractivity of impulsive Hopfield neural networks with time delays. ...
Robust stability for uncertain stochastic neural network with delay and impulses
This paper devotes to the stochastic robust stability of uncertain neural networks with time-varying delay and impulses. By using Lyapunov function and stochastic analysis approaches, a sufficient condition is derived in terms of linear matrix ...






Comments