Coordinating UAVs and AUVs for Oceanographic Field Experiments: Challenges and Lessons Learned

• Type: Article in International Conference Proceedings Book
• Date: 2014-09-29

Authors

José Queirós Pinto (Author) FEUP; Margarida Faria (Author) FEUP; Frédéric Py (Author) FEUP; Kanna Rajan (Author) FEUP; João Tasso Sousa (Author) FEUP; João Fortuna (Author) FEUP; Ricardo Martins (Author) FEUP; Tor Arne Johansen (Author) Other

Conference proceedings International

Title: Proceedings - IEEE International Conference on Robotics and Automation

Pages: 6606-6611

2014 IEEE International Conference on Robotics and Automation, ICRA 2014

31 May 2014 through 7 June 2014

Indexing

ISI Web of Knowledge - 15 Citations

Scopus - 28 Citations

Other information

Authenticus ID: P-00G-4Y5

DOI: 10.1109/icra.2014.6907834

Abstract (EN): Obtaining synoptic observations of dynamic ocean phenomena such as fronts, eddies, oxygen minimum zones and blooms has been challenging primarily due to the large spatial scales involved. Traditional methods of observation with manned ships are expensive and, unless the vessel can survey at high-speed, unrealistic. Autonomous underwater vehicles (AUVs) are robotic platforms that have been making steady gains in sampling capabilities and impacting oceanographic observations especially in coastal areas. However, their reach is still limited by operating constraints related to their energy sources. Unmanned aerial vehicles (UAVs) recently introduced in coastal and polar oceanographic experiments have added to the mix in observation strategy and methods. They offer a tantalizing opportunity to bridge such scales in operational oceanography by coordinating with AUVs in the water-column to get in-situ measurements. In this paper, we articulate the principal challenges in operating UAVs with AUVs making synoptic observations for such targeted water-column sampling. We do so in the context of autonomous control and operation for networked robotics and describe novel experiments while articulating the key challenges and lessons learned.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 6