Abstract
This paper presents the functional architecture of a flight endurance enhancement system that is suitable for the operation of battery-powered Unmanned Aerial Systems (UAS) in maritime and coastal regions. The flight duration problem is subject of various research efforts; different techniques have arisen to address different aspects aiming to prolong the airborne time with minimum resources. This is a great challenge for low-cost platforms that are typically operated with Lithium-Polymer (LiPo) batteries, which have inherent cost and weight restrictions, and also they have not reached sufficient safety and reliability levels to operate in hazardous environments, such as the ocean. This paper depicts the architecture of novel system for flight endurance enhancement. This system is based on Atmospheric Energy Harvesting (AEH) techniques for exploitation of spatial and temporal wind gradients, which is a bio-mimetic principle observed in the flight of albatrosses in the southern ocean. This paper summarizes the high level and low level functional architecture of the proposed modules, including those that have been fully designed, implemented and tested (wind estimation gen1, wind feature identification, communication framework, trajectory generation) and those that are still subject for research, e.g. trajectory tracking and the next generation wind identification system.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
AR5 Life Ray. http://airray.tekever.com/ar5
RAPSODY - Remote Airborne Platform with Satellite Oversight DependencY — ESA’s ARTES Applications. https://artes-apps.esa.int/projects/rapsody
STEAM - Ship’s Sulfur Trails Emissions Aerial Measurements — ESA’s ARTES Applications. https://artes-apps.esa.int/projects/steam
3DR: Pixhawk Autopilot, Quick Start Guide (2014). https://goo.gl/lhi0jx
Balampanis, F., Maza, I., Ollero, A.: Coastal areas division and coverage with multiple UAVs for remote sensing. Sensors 17(4), 808 (2017). https://doi.org/10.3390/s17040808. (Switzerland)
Balampanis, F., Maza, I., Ollero, A.: Spiral-like coverage path planning for multiple heterogeneous UAS operating in coastal regions. In: 2017 International Conference on Unmanned Aircraft Systems (ICUAS), Miami, FL, USA (2017)
Bower, G.C.: Boundary Layer Dynamic Soaring for Autonomous Aircraft: Design and Validation. Ph.D. thesis, Stanford University (2011). https://goo.gl/gNoS1S
Braga, J., Alessandretti, A., Aguiar, A., Sousa, J.: A feedback motion strategy applied to a UAV to work as an autonomous relay node for maritime operations. In: 2017 International Conference on Unmanned Aircraft Systems (ICUAS), Miami, FL, USA (2017)
Carter, D.J.T.: Prediction of wave height and period for a constant wind velocity using the JONSWAP results. Ocean Eng. 9(1), 17–33 (1982)
Hardkernel Co., Ltd.: Odroid Platforms, ODROID-C2 (2013). http://goo.gl/8nQVKO
Klimkowska, A., Lee, I., Choi, K.: Possibilities of Uas for maritime monitoring. In: The international Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 2016 XXIII ISPRS Congress, vol. XLI-B1 (2016). https://goo.gl/M2iuCK
O’Young, S., Hubbard, P.: Raven: a maritime surveillance project using small UAV. In: 2007 IEEE Conference on Emerging Technologies and Factory Automation (EFTA 2007), pp. 904–907 (2007)
Richardson, P.L.: How do albatrosses fly around the world without flapping their wings? Progress in Oceanography (2010). https://goo.gl/K8Puxi
Rodriguez, L., Balampanis, F., Cobano, J.A., Maza, I., Ollero, A.: Wind efficient path planning and reconfiguration of UAS in future ATM. In: Twelfth USA/Europe Air Traffic Management Research and Development Seminar (ATM 2017), p. 140, Seattle, WA, USA (2017)
Rodriguez, L., Cobano, J.A., Ollero, A.: Wind field estimation and identification having shear wind and discrete gusts features with a small UAS. In: 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 5638–5644, Dajeon, Korea (2016)
Rodriguez, L., Cobano, J.A., Ollero, A.: Small UAS-based wind feature identification system part 1: integration and validation. Sensors 17(1), 8 (2017)
Rodriguez, L., Cobano, J.A., Ollero, A.: Smooth trajectory generation for wind field exploitation with a small UAS. In: 2017 International Conference on Unmanned Aircraft Systems (ICUAS), pp. 1241–1249, Miami, FL, USA (2017)
Scrosati, B., Hassoun, J., Sun, Y.K.: Lithium-ion batteries. a look into the future. Energy Environ. Sci. 4(9), 3287 (2011). http://xlink.rsc.org/?DOI=c1ee01388b
Wenz, A., Johansen, T.A.: Estimation of wind velocities and aerodynamic coefficients for UAVs using standard autopilot sensors and a moving horizon estimator. In: 2017 International Conference on Unmanned Aircraft Systems (ICUAS), pp. 1267–1276, Miami, FL, USA (2017)
Wenz, A., Johansen, T.A., Cristofaro, A.: Combining model-free and model-based angle of attack estimation for small fixed-wing UAVs using a standard sensor suite. In: 2016 International Conference on Unmanned Aircraft Systems, ICUAS 2016, pp. 624–632 (2016). https://doi.org/10.1109/ICUAS.2016.7502583
Acknowledgment
This work has been supported by the MarineUAS project (MSCA-ITN-2014-642153), funded by the European Commission under the Horizon 2020 Programme as part of the Marie Sklodowska Curie Actions and by the AEROMAIN project (DPI2014-5983-C2-1-R), funded by the Science and Innovation Ministry of the Spanish Government.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG
About this paper
Cite this paper
RodrÃguez, L., Cobano, J.A., Ollero, A. (2018). Architecture of a Flight Endurance Enhancement System for Maritime Operations with Fixed Wing UAS. In: Ollero, A., Sanfeliu, A., Montano, L., Lau, N., Cardeira, C. (eds) ROBOT 2017: Third Iberian Robotics Conference. ROBOT 2017. Advances in Intelligent Systems and Computing, vol 693. Springer, Cham. https://doi.org/10.1007/978-3-319-70833-1_15
Download citation
DOI: https://doi.org/10.1007/978-3-319-70833-1_15
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-70832-4
Online ISBN: 978-3-319-70833-1
eBook Packages: EngineeringEngineering (R0)