There exist several application scenarios of mobile ad hoc networks (MANET) in which the nodes need to locate a target or surround it. Severe resource constraints in MANETs call for energy efficient target localization and collaborative navigation. Centralized control of MANET nodes is not an attractive solution due to its high network utilization that can result in congestions and delays. In nature, many colonies of biological species (such as a flock of birds) can achieve effective collaborative navigation without any centralized control. Particle swarm optimization (PSO), a popular swarm intelligence approach that models social dynamics of a biological swarm is proposed in this paper for network-centric target localization in MANETs that are enhanced by mobile robots. Simulation study of two application scenarios is conducted. While one scenario focuses on quick target localization, the other aims at convergence of MANET nodes around the target. Reduction of swarm size during PSO search is proposed for accelerated convergence. The results of the study show that the proposed algorithm is effective in network-centric collaborative navigation. Emergence of converging behavior of MANET nodes is observed.


Engineering Management and Systems Engineering

Second Department

Electrical and Computer Engineering


National Science Foundation (U.S.)

Keywords and Phrases

Mobile Ad Hoc Networks (MANETs); Ad Hoc Networks; Mobile Communication; Mobile Robots; Multi-Robot Systems; Network-Centric Control; Particle Swarm Optimization (PSO); Resource Allocation; Target Localization; Wireless Sensor Networks (WSNs)

Document Type

Article - Conference proceedings

Document Version

Final Version

File Type





© 2008 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.

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