Multiagent Information Fusion and Cooperative Control in Target Search

This paper addresses cooperative search for multiple stationary ground targets by a group of unmanned aerial vehicles with limited sensing and communication capabilities. The whole surveillance region is partitioned into cells where each cell is associated with a probability of target existence with...

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Bibliographic Details
Published in:IEEE transactions on control systems technology 2013-07, Vol.21 (4), p.1223-1235
Main Authors: Hu, Jinwen, Xie, Lihua, Lum, Kai-Yew, Xu, Jun
Format: Article
Language:English
Subjects:
Agents (artificial intelligence)
Algorithms
Bayesian analysis
Bayesian methods
Computer simulation
Convergence
Cooperative control
distributed fusion
multiagent network
Multiagent systems
Network topology
Path planning
Sampling
Searching
Sensors
Studies
Surveillance
target search
Topology
Transformations
Unmanned aerial vehicles
unmanned aerial vehicles (UAVs)
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Summary:This paper addresses cooperative search for multiple stationary ground targets by a group of unmanned aerial vehicles with limited sensing and communication capabilities. The whole surveillance region is partitioned into cells where each cell is associated with a probability of target existence within the cell, which constitutes a probability map for the whole region. Each agent keeps an individual probability map and updates the map individually with measurements according to Bayesian rule. A nonlinear transformation of the probability map is introduced to simplify the computation by linearizing the Bayesian update. A consensus-like distributed fusion scheme is proposed for multiagent map fusion. We prove that all the individual probability maps converge to the same one that reflects the true existence or nonexistence of targets within each cell. Coverage and topology control algorithms are designed for the path planning of mobile agents. Moreover, the performance of the fusion scheme for asynchronous implementations of sampling and communication is analyzed. Finally, the effectiveness of the proposed algorithms is illustrated via simulations.
ISSN:1063-6536
1558-0865
DOI:10.1109/TCST.2012.2198650