Title
Multi-UAV target search using decentralized gradient-based negotiation with expected observation
Abstract
This paper presents a novel approach for the coordination of a team of autonomous sensor platforms searching for lost targets under uncertainty. A real-time receding horizon controller in continuous action space is developed based on a decentralized gradient-based optimization algorithm and by using the expected observation as an estimate of future rewards. The expected observation is a cost-to-go heuristic that estimates the goodness of the states that the platforms could reach. It permits the decision making algorithm to take into account the information on the whole environment, reducing the time needed to detect the target. The heuristic, modeled as a sensor, allows us to develop a new team utility function with low computational cost and high performance. It can be applied to challenging scenarios such as multi-target search with complex and non-uniform target probability distributions. Through simulation and statistical analysis, we show the advantages of using the expected observation heuristic in multi-vehicle coordination for search applications.
Year
DOI
Venue
2014
10.1016/j.ins.2014.05.054
Information Sciences: an International Journal
Keywords
Field
DocType
cooperative search,decentralized decision making,probabilistic reasoning,unmaned air vehicle
Control theory,Mathematical optimization,Heuristic,Probability distribution,Optimization algorithm,Probabilistic logic,Decentralized decision-making,Mathematics,Negotiation,Statistical analysis
Journal
Volume
Issue
ISSN
282
1
0020-0255
Citations 
PageRank 
References 
18
0.76
27
Authors
5
Name
Order
Citations
PageRank
Pablo Lanillos1557.80
Seng Keat Gan21145.69
Eva Besada-Portas317414.02
Gonzalo Pajares469957.18
Salah Sukkarieh51142141.84