Management of multiple heterogeneous UAVs using capability and autonomy visualisation: theory, experiment and result

Chen, Ting (Brendan), Gonzalez, Luis F., Campbell, Duncan A., & Coppin, Gilles (2014) Management of multiple heterogeneous UAVs using capability and autonomy visualisation: theory, experiment and result. In International Conference on Unmanned Aircraft Systems (ICUAS 2014), 27 - 30 May, 2014, Orlando, Florida.

Abstract

The interest in utilising multiple heterogeneous Unmanned Aerial Vehicles (UAVs) in close proximity is growing rapidly. As such, many challenges are presented in the effective coordination and management of these UAVs; converting the current n-to-1 paradigm (n operators operating a single UAV) to the 1-to-n paradigm (one operator managing n UAVs). This paper introduces an Information Abstraction methodology used to produce the functional capability framework initially proposed by Chen et al. and its Level Of Detail (LOD) indexing scale. This framework was validated through comparing the operator workload and Situation Awareness (SA) of three experiment scenarios involving multiple autonomously heterogeneous UAVs. The first scenario was set in a high LOD configuration with highly abstracted UAV functional information; the second scenario was set in a mixed LOD configuration; and the final scenario was set in a low LOD configuration with maximal UAV functional information. Results show that there is a significant statistical decrease in operator workload when a UAV’s functional information is displayed at its physical form (low LOD - maximal information) when comparing to the mixed LOD configuration.

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ID Code: 71026
Item Type: Conference Paper
Refereed: Yes
Additional URLs:
Keywords: Supervisory control, heterogeneous UAVs, UAV management
Subjects: Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > AEROSPACE ENGINEERING (090100)
Divisions: Current > Research Centres > Australian Research Centre for Aerospace Automation
Current > Schools > School of Electrical Engineering & Computer Science
Current > Institutes > Institute for Future Environments
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2014 [please consult the author]
Deposited On: 06 May 2014 23:24
Last Modified: 02 Aug 2014 09:17

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