Real-time Experiment of Feature Tracking/Mapping using a low-cost Vision and GPS/INS System on an UAV platform

Jonghyuk Kim, Matthew Ridley, Salah Sukkarieh, Eric Nettleton

Advanced Information Processing Department, Advanced Technology Centre, BAE Systems, UK.
ARC Centre of Excellence for Autonomous Systems, The University of Sydney, Australia.

DOI:                 

Abstract

This paper presents the real-time results of an air-to-ground feature tracking algorithm using a passive vision camera and a low-cost GPS/INS navigation system on a UAV (Uninhabited Air Vehicle) platform. The vision payload is able to observe a number of ground features, and the GPS/INS navigation system is used in conjunction with a waypoints-based guidance and flight control module. Due to limited processing resources, the vision node employs a simple but fast method of point based feature extraction algorithm. The feature tracking performance is greatly affected by the accuracy of the onboard navigation system. Conversely though, it can be used as a performance indicator of the navigation filter by comparing it with the truth feature location and some simple geometry. This paper will present the results of targeting performance against known location of features, and hence verifying the accuracy of the real time GPS/INS system

Keywords

low cost GPS/INS, vision sensor, features tracking, real-time navigation, UAV

Conflicts of Interest

The authors declare no conflicts of interest.

References

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