Marsupial System Datasets
We present a dataset that englobes four different experiments in indoor scenarios carried out with our Marsupial System described in our paper submitted to Drones: S. Martinez-Rozas, D. Alejo, J. J. Carpio, F. Caballero and L. Merino. "Long Duration Inspection of GNSS-Denied Environments with a Tethered UAV-UGV Marsupial System". Each experiment was designed with a purpose in mind. The first presented experiment was designed to test the flight duration of our proposed system. Experiments 2 and 3 are designed to test our localization and trajectory tracking system, respectively. Finally, the last experiment is an emulated inspection test.
The datasets are timestamped and stored by means of the well-known Robot Operating System (ROS) bag package. The contents of the different bags is detailed in the contents section.
Copyright
All datasets and benchmarks on this page are copyright by us and published under the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 License. This means that you must attribute the work in the manner specified by the authors, you may not use this work for commercial purposes and if you alter, transform, or build upon this work, you may distribute the resulting work only under the same license.
Citation
Please cite our preprint that describes our Marsupial System if you use the dataset for your research. It would be more than welcome!!
Plain text
S. Martinez-Rozas, D. Alejo, J. J. Carpio, F. Caballero and L. Merino. "Long Duration Inspection of GNSS-Denied Environments with a Tethered UAV-UGV Marsupial System".
Bibtex
@misc{martínezrozas2025longdurationinspectiongnssdenied, title={Long Duration Inspection of GNSS-Denied Environments with a Tethered UAV-UGV Marsupial System}, author={Simón Martínez-Rozas and David Alejo and José Javier Carpio and Fernando Caballero and Luis Merino}, year={2025}, eprint={2505.23457}, archivePrefix={arXiv}, primaryClass={cs.RO}, url={https://arxiv.org/abs/2505.23457}, }
Acknowledgements
This work is partially supported by Programa Operativo FEDER Andalucia 2014-2020, Consejeria de Economía, Conocimiento y Universidades (DeepBot, PY20_00817) and the Insertion project, funded by MCIN with grant number PID2021-127648OB-C31.
