DocumentCode
184018
Title
Continuous-time intruder isolation using Unattended Ground Sensors on graphs
Author
Hua Chen ; Kalyanam, Krishnamoorthy ; Wei Zhang ; Casbeer, D.
Author_Institution
Dept. of Electr. & Comput. Eng., Ohio State Univ., Columbus, OH, USA
fYear
2014
fDate
4-6 June 2014
Firstpage
5270
Lastpage
5275
Abstract
This paper studies the continuous-time intruder isolation problem on a general road network graph under delayed information scenario. Several Unattended Ground Sensors (UGSs) are pre-installed along certain edges of the graph for detecting intruder motion and recording the detection time. Measurements of a UGS can only be obtained when the UAV is within its communication range. The goal of this paper is to find the optimal path for the UAV to follow in order to capture the intruder within the shortest time, based on the delayed information from the visited UGSs. We propose an unfolding strategy to transform the road network graph to a decision tree incorporating delayed measurement information. Based on the decision tree, both optimal and sub-optimal min-max solutions are developed. Several interesting properties of the corresponding optimal value function are also derived. Numerical simulations based on a real road network are presented to demonstrate the effectiveness of the proposed strategies.
Keywords
autonomous aerial vehicles; decision trees; delays; minimax techniques; network theory (graphs); optimal control; roads; UAV; UGS measurement; communication range; continuous time intruder isolation; decision tree; delayed information; delayed measurement; intruder motion detection; numerical simulation; optimal min-max solution; optimal value function; road network graph; shortest time; unattended ground sensor; unfolding strategy; Aerospace electronics; Decision trees; Games; Optimal control; Roads; Sensors; Uncertainty; Autonomous systems; Control applications;
fLanguage
English
Publisher
ieee
Conference_Titel
American Control Conference (ACC), 2014
Conference_Location
Portland, OR
ISSN
0743-1619
Print_ISBN
978-1-4799-3272-6
Type
conf
DOI
10.1109/ACC.2014.6858895
Filename
6858895
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