Imperial College London
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ProfessorEricKerrigan

Faculty of Engineering, Department of Electrical and Electronic Engineering

Professor of Control and Optimization
 
 
 
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Contact

 

+44 (0)20 7594 6343e.kerrigan Website

 
 
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Assistant

 

Mrs Raluca Reynolds +44 (0)20 7594 6281

 
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Location

 

1114Electrical EngineeringSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Thammawichai:2018:10.1109/TAES.2017.2761139,
author = {Thammawichai, M and Baliyarasimhuni, SP and Kerrigan, EC and Sousa, JB},
doi = {10.1109/TAES.2017.2761139},
journal = {IEEE Transactions on Aerospace and Electronic Systems},
pages = {601--615},
title = {Optimizing communication and computation for multi-UAV information gathering applications},
url = {http://dx.doi.org/10.1109/TAES.2017.2761139},
volume = {54},
year = {2018}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Typical mobile agent networks, such as multi-unmanned aerial vehicle (UAV) systems, are constrained by limited resources: energy, computing power, memory and communication bandwidth. In particular, limited energy affects system performance directly, such as system lifetime. Moreover, it has been demonstrated experimentally in the wireless sensor network literature that the total energy consumption is often dominated by the communication cost, i.e., the computational and the sensing energy are small compared to the communication energy consumption. For this reason, the lifetime of the network can be extended significantly by minimizing the communication distance as well as the amount of communication data, at the expense of increasing computational cost. In this paper, we aim at attaining an optimal tradeoff between the communication and the computational energy. Specifically, we propose a mixed-integer optimization formulation for a multihop hierarchical clustering-based self-organizing UAV network incorporating data aggregation, to obtain an energy-efficient information routing scheme. The proposed framework is tested on two applications, namely target tracking and area mapping. Based on simulation results, our method can significantly save energy compared to a baseline strategy, where there is no data aggregation and clustering scheme.
AU  - Thammawichai,M
AU  - Baliyarasimhuni,SP
AU  - Kerrigan,EC
AU  - Sousa,JB
DO  - 10.1109/TAES.2017.2761139
EP  - 615
PY  - 2018///
SN  - 0018-9251
SP  - 601
TI  - Optimizing communication and computation for multi-UAV information gathering applications
T2  - IEEE Transactions on Aerospace and Electronic Systems
UR  - http://dx.doi.org/10.1109/TAES.2017.2761139
UR  - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000429990900006&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR  - http://hdl.handle.net/10044/1/69528
VL  - 54
ER  -
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