DocumentCode :
2831923
Title :
Cooperative graph-based model predictive search
Author :
Riehl, James R. ; Collins, Gaemus E. ; Hespanha, João P.
Author_Institution :
Univ. of California, Santa Barbara
fYear :
2007
fDate :
12-14 Dec. 2007
Firstpage :
2998
Lastpage :
3004
Abstract :
We present a receding-horizon cooperative search algorithm that jointly optimizes routes and sensor orientations for a team of autonomous agents searching for a mobile target. By sampling the region of interest at locations with high target probability, we reduce the continuous search problem to an optimization on a finite graph. Paths are computed on this graph using a receding horizon approach, in which the horizon is a fixed number of waypoints. To facilitate a fair comparison between paths of varying length on a non-uniform graph, we use an optimization criterion corresponding to the probability of finding the target per unit time. Using this algorithm, we show that the team discovers the target in finite time with probability one. Simulations verify that this algorithm makes effective use of agents and performs significantly better than previously proposed search algorithms. We have also successfully tested this search algorithm on a physical system consisting of two UAVs with gimbal-mounted cameras.
Keywords :
aerospace robotics; decentralised control; graph theory; mobile robots; multi-robot systems; predictive control; remotely operated vehicles; search problems; UAV; cooperative graph-based model predictive search; finite graph; optimization criterion; receding-horizon cooperative search algorithm; Autonomous agents; Cameras; Military computing; Piecewise linear approximation; Prediction algorithms; Predictive models; Sampling methods; Search problems; System testing; USA Councils;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Decision and Control, 2007 46th IEEE Conference on
Conference_Location :
New Orleans, LA
ISSN :
0191-2216
Print_ISBN :
978-1-4244-1497-0
Electronic_ISBN :
0191-2216
Type :
conf
DOI :
10.1109/CDC.2007.4435025
Filename :
4435025
Link To Document :
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