@INPROCEEDINGS{8324795, 
author={T. Li and S. Hailes and S. Julier and M. Liu}, 
booktitle={2017 IEEE International Conference on Robotics and Biomimetics (ROBIO)}, 
title={UAV-based SLAM and 3D reconstruction system}, 
year={2017}, 
volume={}, 
number={}, 
pages={2496-2501}, 
abstract={3D reconstructing a landscape is a prevalent problem that attracts a lot of interest in recent years. This project intended to verify whether the hypothesis of a UAV-based SLAM and 3D reconstruction system is practical. A GPS-Fused SLAM system is built based on ORB-SLAM. Inverse depth is also implemented to make the system suitable for a UAV-based platform. Meanwhile, REMODE is a depth filter and is tested as not being well enough as a dense mapping module. In the end, PMVS is implemented to build a dense map of the environment which produces a reasonable result. The small-scale-scene experiments produce the total error ratio of 5.60% in the x-y plane and 6.59% in the z axis.}, 
keywords={SLAM (robots);autonomous aerial vehicles;image reconstruction;mobile robots;robot vision;3D reconstruction system;GPS-Fused SLAM system;ORB-SLAM;UAV;Cameras;Global Positioning System;Image reconstruction;Simultaneous localization and mapping;Solid modeling;Synthetic aperture radar;Three-dimensional displays;GPS;PMVS;SLAM;UAV}, 
doi={10.1109/ROBIO.2017.8324795}, 
ISSN={}, 
month={Dec},}