Abstract
This paper describes an algorithmic solution for simple and efficient underwater orientation and depth control. Maintaining a position with an underwater robot is a difficult task. In the case of an Autonomous Underwater Vehicles (AUVs), not only the underwater conditions, but also the environmental effects off the surface need to be considered. There is a large number of algorithms have been designed by researchers based on computer vision, sensor fusion, etc. to estimate the location precisely, yet most of them are specific for the given hardware. Our solution employs a multi-sensor fusion based algorithm, where the data is taken from magnetic and pressure sensors. A PID controller was designed and implemented to ensure proper orientation keeping and depth control in rippling water. The solution has been tested in various environments, and successfully used during the marine challenges of the euRathlon 2015 competition.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Zhao, S., Yuh, J.: Experimental study on advanced underwater robot control. IEEE Trans. Rob. 21(4), 695–703 (2005)
Santhakumar, M., Asokan, T.: Non-linear adaptive control system for an underactuated autonomous underwater vehicle using dynamic state feedback. Int. J. Recent Trend Eng. 2, 384–389 (2009)
Carreras, M., et al.: Sparus II, design of a lightweight hovering AUV. In: Martech 5th International Workshop on Marine Technology, SARTI (2013)
Quigley, M., et al.: ROS: an open-source robot operating system. In: ICRA Workshop on Open Source Software, p. 5 (2009)
Prats, M., et al.: An open source tool for simulation and supervision of underwater intervention missions. In: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 2577–2582. IEEE (2013)
Takacs, B., Doczi, R., Suto, B., Kallo, J., Varkonyi, T., Haidegger, T., Kozlovszky, M.: Extending AUV response robot capabilities to solve standardized test methods. Acta Polytech. Hung. 13(1), 157–170 (2016)
Available tools in Robot Operating System. http://wiki.ros.org/Tools
Ahn, K.K., Dinh, Q.T.: Online tuning fuzzy PID controller using robust extended Kalman filter. J. Process Control 19(6), 1011–1023 (2009)
Acknowledgement
Authors would like to thank NATO Centre for Maritime Research and Organization (CMRE) for the opportunity to access and use the Sparus II AUV during the euRathlon competition, and also the friendly support of NIST and University of Girona (UdG). Financial support for this work was provided by the University Research and Innovation Center (EKIK) of Óbuda University.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this paper
Cite this paper
Dóczi, R., Takács, B., Sütő, B., Haidegger, T., Kozlovszky, M., Tar, J.K. (2017). Orientation and Depth Control in Rippling Water for an Autonomous Underwater Robot. In: Rodić, A., Borangiu, T. (eds) Advances in Robot Design and Intelligent Control. RAAD 2016. Advances in Intelligent Systems and Computing, vol 540. Springer, Cham. https://doi.org/10.1007/978-3-319-49058-8_36
Download citation
DOI: https://doi.org/10.1007/978-3-319-49058-8_36
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-49057-1
Online ISBN: 978-3-319-49058-8
eBook Packages: EngineeringEngineering (R0)