Collaborative Sensing by Unmanned Aerial Vehicles

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Teacy, W. T. L., Nie, J., McClean, S., Parr, G. ORCID: https://orcid.org/0000-0002-9365-9132, Hailes, S., Julier, S., Trigoni, N. and Cameron, S. (2009) Collaborative Sensing by Unmanned Aerial Vehicles. In: 3rd International Workshop on Agent Technology for Sensor Networks. UNSPECIFIED, HUN, pp. 13-16.

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Abstract

In many military and civilian applications, Unmanned Aerial Vehicles (UAVs) provide an indispensable platform for gathering information about the situation on the ground. In particular, they have the potential to revolutionize the way in which information is collected, fused and disseminated. These advantages are greatly enhanced if swarms of multiple UAVs are used, since this enables the collection of data from multiple vantage points using multiple sensors. However, enhancements to overall operational performance can be realised only if the platforms have a high degree of autonomy, which is achieved through machine intelligence. With this in mind, we report on our recently launched project, SUAAVE (Sensing, Unmanned, Autonomous, Aerial VEhicles), which seeks to develop and evaluate a fully automated sensing platform consisting of multiple UAVs. To achieve this goal, we will take a multiply disciplinary approach, focusing on the complex dependencies that exist between tasks such as data fusion, ad-hoc wireless networking, and multi-agent co-ordination. In this position paper, we highlight the related work in this area and outline our agenda for future work.

Item Type:	Book Section
Uncontrolled Keywords:	uav,uav swarms,sensor networks,decentralized control
Faculty \ School:	Faculty of Science > School of Computing Sciences
UEA Research Groups:	Faculty of Science > Research Groups > Smart Emerging Technologies Faculty of Science > Research Groups > Cyber Security Privacy and Trust Laboratory Faculty of Science > Research Groups > Data Science and AI
Related URLs:	http://eprints.soton.ac.uk/267290/
Depositing User:	Pure Connector
Date Deposited:	16 Nov 2016 13:00
Last Modified:	10 Dec 2024 01:11
URI:	https://ueaeprints.uea.ac.uk/id/eprint/61381
DOI:

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