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Underwater Robotics Competitions: The European Robotics League Emergency Robots Experience With FeelHippo AUV
- Source :
- Frontiers in Robotics and AI, Vol 7 (2020)
- Publication Year :
- 2020
- Publisher :
- Frontiers Media S.A., 2020.
-
Abstract
- Underwater robots are nowadays employed for many different applications; during the last decades, a wide variety of robotic vehicles have been developed by both companies and research institutes, different in shape, size, navigation system, and payload. While the market needs to constitute the real benchmark for commercial vehicles, novel approaches developed during research projects represent the standard for academia and research bodies. An interesting opportunity for the performance comparison of autonomous vehicles lies in robotics competitions, which serve as an useful testbed for state-of-the-art underwater technologies and a chance for the constructive evaluation of strengths and weaknesses of the participating platforms. In this framework, over the last few years, the Department of Industrial Engineering of the University of Florence participated in multiple robotics competitions, employing different vehicles. In particular, in September 2017 the team from the University of Florence took part in the European Robotics League Emergency Robots competition held in Piombino (Italy) using FeelHippo AUV, a compact and lightweight Autonomous Underwater Vehicle (AUV). Despite its size, FeelHippo AUV possesses a complete navigation system, able to offer good navigation accuracy, and diverse payload acquisition and analysis capabilities. This paper reports the main field results obtained by the team during the competition, with the aim of showing how it is possible to achieve satisfying performance (in terms of both navigation precision and payload data acquisition and processing) even with small-size vehicles such as FeelHippo AUV.
Details
- Language :
- English
- ISSN :
- 22969144
- Volume :
- 7
- Database :
- Directory of Open Access Journals
- Journal :
- Frontiers in Robotics and AI
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.01d7ba85d243d1b0070e5bbf1b57c3
- Document Type :
- article
- Full Text :
- https://doi.org/10.3389/frobt.2020.00003