Volume 18, Issue 7 (2018)                   Modares Mechanical Engineering 2018, 18(7): 68-78 | Back to browse issues page

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Khorrambakht E, Roshanian J, Khodabakhsh A H. Performance Study of Distributed Control Algorithm for Cooperative Search using Multi-Agent System. Modares Mechanical Engineering. 2018; 18 (7) :68-78
URL: http://journals.modares.ac.ir/article-15-14870-en.html
1- Flight Dynamics & Control, Aerospace Engineering, K. N. Toosi University of Technology, Tehran, Iran
2- Department of Aerospace Engineering, K. N. Toosi University of Technology, Tehran, Iran
3- Department of Aerospace Engineering, Sharif University of Technology, Tehran, Iran
Abstract:   (1815 Views)
Vastness of operation airspace and uncertain environment in aerial search missions, makes utilizing multiple intelligent agents more preferable to integrated centralized systems due to robustness, parallel computing structure, scalability, and cost optimality of distributed systems. Cooperative search missions require the search space to be divided properly between agents. In order to minimize the uncertainty, the agents will calculate the best path in the assigned space partition. According to the communication topology, environmental information and the near-future decisions are shared between agents. In this paper, cooperative search using multiple UAVs has been considered. First, mathematical representation of the search space, kinematic and sensor model of UAVs, and communication topology have been presented. Then, an approach has been proposed to update and share information using the Bayes’ rule. Afterwards, path planning problem has been solved using different optimization algorithms namely First-order Gradient, Conjugate Gradient, Sequential Quadratic Programming, and Interior Point Algorithm. Finally, the performance of these algorithms have been compared according to mean uncertainty reduction and target detection time.
Full-Text [PDF 5659 kb]   (206 Downloads)    
Article Type: Research Article |
Received: 2018/02/11 | Accepted: 2018/09/25 | Published: 2018/09/25

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