Title :
Adaptive models of pop-up threats for multi-agent persistent area denial
Author :
Subramanian, Shankar K. ; Cruz, Jose B.
Author_Institution :
Dept. of Electr. Eng., Ohio State Univ., Columbus, OH, USA
Abstract :
Adversarial ground assets that become observable for short durations are modeled as adaptive Markov chains. Multiple Unmanned Air Vehicles (UAVs) are cooperatively deployed to reach the threats in the shortest time. This paper describes the threat modeling and movement strategies for the UAVs. Simulation experiments indicate that this approach is appropriate for addressing persistent area denial problems.
Keywords :
Markov processes; modelling; remotely operated vehicles; simulation; adaptive Markov chains; adaptive models; multiagent persistent area; multiple unmanned air vehicles; popup threats; threat modeling; Analytical models; Equations; Kinematics; Monitoring; Predictive models; Uninterruptible power systems; Unmanned aerial vehicles;
Conference_Titel :
Decision and Control, 2003. Proceedings. 42nd IEEE Conference on
Print_ISBN :
0-7803-7924-1
DOI :
10.1109/CDC.2003.1272614