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Title: NTU VIRAL: a visual-inertial-ranging-lidar dataset, from an aerial vehicle viewpoint
Authors: Nguyen, Thien-Minh
Yuan, Shenghai
Cao, Muqing
Lyu, Yang
Nguyen, Thien Hoang
Xie, Lihua
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2021
Source: Nguyen, T., Yuan, S., Cao, M., Lyu, Y., Nguyen, T. H. & Xie, L. (2021). NTU VIRAL: a visual-inertial-ranging-lidar dataset, from an aerial vehicle viewpoint. International Journal of Robotics Research, 41(3), 270-280.
Journal: International Journal of Robotics Research
Abstract: In recent years, autonomous robots have become ubiquitous in research and daily life. Among many factors, public datasets play an important role in the progress of this field, as they waive the tall order of initial investment in hardware and manpower. However, for research on autonomous aerial systems, there appears to be a relative lack of public datasets on par with those used for autonomous driving and ground robots. Thus, to fill in this gap, we conduct a data collection exercise on an aerial platform equipped with an extensive and unique set of sensors: two 3D lidars, two hardware-synchronized global-shutter cameras, multiple Inertial Measurement Units (IMUs), and especially, multiple Ultra-wideband (UWB) ranging units. The comprehensive sensor suite resembles that of an autonomous driving car, but features distinct and challenging characteristics of aerial operations. We record multiple datasets in several challenging indoor and outdoor conditions. Calibration results and ground truth from a high-accuracy laser tracker are also included in each package. All resources can be accessed via our webpage
ISSN: 0278-3649
DOI: 10.1177/02783649211052312
DOI (Related Dataset): 10.21979/N9/X39LEK
Rights: © 2021 The Author(s), (published by SAGE Publications). All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
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