AUV-Based Plume Tracking

This paper presents a simulation study of an autonomous underwater vehicle AUV navigation system operating in a GPS-denied environment. The AUV navigation method makes use of underwater transponder positioning and requires only one transponder. A multirate unscented Kalman filter is used to determine the AUV orientation and position by fusing high-rate sensor data and low-rate information. The paper also proposes a gradient-based, efficient, and adaptive novel algorithm for plume boundary tracking missions. The algorithm follows a centralized approach and it includes path optimization features based on gradient information. The proposed algorithm is implemented in simulation on the AUV-based navigation system and successful boundary tracking results are obtained.

[1]  S. M. Smith,et al.  Enhancement of the inertial navigation system for the Morpheus autonomous underwater vehicles , 2001 .

[2]  Sajad Saeedi,et al.  AUV Navigation and Localization: A Review , 2014, IEEE Journal of Oceanic Engineering.

[3]  K. Gade,et al.  Underwater transponder positioning and navigation of autonomous underwater vehicles , 2009, OCEANS 2009.

[4]  Peter F. McGuire,et al.  Simulation of aided AUV navigation and adaptive plume tracking , 2014, 2014 IEEE 27th Canadian Conference on Electrical and Computer Engineering (CCECE).

[5]  Andrea L. Bertozzi,et al.  Environmental boundary tracking and estimation using multiple autonomous vehicles , 2007, 2007 46th IEEE Conference on Decision and Control.

[6]  James G. Bellingham,et al.  A peak-capture algorithm used on an autonomous underwater vehicle in the 2010 Gulf of Mexico oil spill response scientific survey , 2011, J. Field Robotics.

[7]  Oddvar Hallingstad,et al.  Towards Model-Aided Navigation of Underwater Vehicles , 2007 .

[8]  Aiqun Zhang,et al.  Behavior-based control of an autonomous underwater vehicle for adaptive plume mapping , 2011, 2011 2nd International Conference on Intelligent Control and Information Processing.

[9]  John J. Leonard,et al.  Efficient AUV navigation fusing acoustic ranging and side-scan sonar , 2011, 2011 IEEE International Conference on Robotics and Automation.

[10]  Yuanyuan Zhao,et al.  Autonomous Underwater Vehicle Navigation , 2010, IEEE Journal of Oceanic Engineering.

[11]  Rudolph van der Merwe,et al.  The unscented Kalman filter for nonlinear estimation , 2000, Proceedings of the IEEE 2000 Adaptive Systems for Signal Processing, Communications, and Control Symposium (Cat. No.00EX373).

[12]  Gaurav S. Sukhatme,et al.  Towards marine bloom trajectory prediction for AUV mission planning , 2010, 2010 IEEE International Conference on Robotics and Automation.

[13]  Carlos Silvestre,et al.  Embedded Vehicle Dynamics Aiding for USBL/INS Underwater Navigation System , 2014, IEEE Transactions on Control Systems Technology.

[14]  C.J. Cannell,et al.  Boundary Tracking and Rapid Mapping of A Thermal Plume Using an Autonomous Vehicle , 2006, OCEANS 2006.

[15]  O Hegrenaes,et al.  Model-Aided INS With Sea Current Estimation for Robust Underwater Navigation , 2011, IEEE Journal of Oceanic Engineering.

[16]  Hanumant Singh,et al.  Experimental Results in Synchronous-Clock One-Way-Travel-Time Acoustic Navigation for Autonomous Underwater Vehicles , 2007, Proceedings 2007 IEEE International Conference on Robotics and Automation.

[17]  Gaurav S. Sukhatme,et al.  Planning and Implementing Trajectories for Autonomous Underwater Vehicles to Track Evolving Ocean Processes Based on Predictions from a Regional Ocean Model , 2010, Int. J. Robotics Res..

[18]  Thor I. Fossen,et al.  Guidance and control of ocean vehicles , 1994 .

[19]  Honghai Liu,et al.  Navigation Technologies for Autonomous Underwater Vehicles , 2008, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[20]  Gaurav S. Sukhatme,et al.  Simultaneous Tracking and Sampling of Dynamic Oceanographic Features with Autonomous Underwater Vehicles and Lagrangian Drifters , 2010, ISER.

[21]  Henrik Schmidt,et al.  Constructing a Distributed AUV Network for Underwater Plume-Tracking Operations , 2011, Int. J. Distributed Sens. Networks.

[22]  Carlos Silvestre,et al.  Improving Aiding techniques for USBL Tightly-Coupled Inertial Navigation System , 2008 .

[23]  Timothy Prestero,et al.  Verification of a six-degree of freedom simulation model for the REMUS autonomous underwater vehicle , 2001 .

[24]  M. Kemp,et al.  Multi-UUV perimeter surveillance , 2004, 2004 IEEE/OES Autonomous Underwater Vehicles (IEEE Cat. No.04CH37578).

[25]  Dariusz Chaberski,et al.  QUANTIZATION ERROR IN TIME-TO-DIGITAL CONVERTERS , 2012 .

[26]  Naomi Ehrich Leonard,et al.  Collective Motion, Sensor Networks, and Ocean Sampling , 2007, Proceedings of the IEEE.

[27]  E. Terrill,et al.  Mapping ocean outfall plumes and their mixing using autonomous underwater vehicles , 2012 .