Fluid field estimation and source localization by dynamic positioning of autonomous underwater sensor nodes
Mechanics
Mechanical Properties of Metallic Materials and their Microstructural Origins
Fluid Mechanics
Final Report Abstract
This project covered the application of AUVs for exploration and monitoring of environmental fields in confined environments. Design of AUV systems, underwater self-localization, and control for information gathering were the main research directions that have been investigated. Solution approaches to these problems were derived, implemented and published. For many cases the project could lift core components to higher technology readiness levels, which was highly appreciated by the scientific community. The AUV platform HippoCampus for monitoring and exploring confined underwater environments was developed within this project. The mechatronic design of the HippoCampus is inspired by recent advances in the field of micro aerial vehicles. One of the biggest challenges in deploying autonomous underwater systems is selflocalization. If an AUV does not know its position, it cannot perform useful operations. This project introduced two approaches for the underwater self-localization problem. Both approaches are passive, i.e. only one-way signal transmission is required. A receiver senses ambient reference signals that are generated by anchored beacons. The first method determines time delays of arrival (TDOAs) of acoustic signals. The signals are generated from a noise distribution, and the TDOAs are determined through cross-correlation. Results demonstrated that selflocalization is possible with the presented approach. The hardware is compact enough to fit into the hull of a micro AUV. The second method was based on the attenuation of EM waves in water. The receiver measures the strength of an ambient EM signal at its own position and determines the ranges to the emitting beacons. Experiments demonstrated that the developed method delivered sufficient localization performance. This is a key step to render autonomous operations in confined underwater environments possible. This research project introduced two novel control approaches for autonomous field exploration with AUVs. A CFD based controller and the PI-GMRF controller. The CFD based controller describes the internal belief by means of discretized Navier-Stokes equations. An EnKF propagates hundreds of slightly varied coarse fluid dynamic simulations through time. Measurements from the mobile sensors are integrated into all ensemble members. A model predictive controller considers covariance minimizing paths. The PI-GMRF controller extends and combines path integral control and GMRF inference. The formulation is based on stochastic optimal control, whereby a belief representation of the environmental fields is maintained within the controller. Field measurements are used to update the GMRF belief. Since GMRFs are stochastic fields, the covariance is readily available for evaluating control actions. An optimal control sequence is approximately obtained by forward sampling along a receding horizon. The approach allows for explicit consideration of system dynamics.
Publications
- CFD in the loop: Ensemble Kalman filtering with underwater mobile sensor networks. In: ASME 2014 33rd International Conference on Ocean, Offshore and Arctic Engineering (OMAE), San Francisco, CA, USA
A. Hackbarth, E. Kreuzer, T. Schroeder
(See online at https://dx.doi.org/10.1115/OMAE2014-24122) - HippoCampus: A Micro Underwater Vehicle for Swarm Applications. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), p. 2258-2263, Hamburg, Germany, 2015
A. Hackbarth, E. Kreuzer, and E. Solowjow
(See online at https://doi.org/10.1109/IROS.2015.7353680) - Towards a Hyperbolic Acoustic One-Way Localization System for Underwater Swarm Robotics. In IEEE International Conference on Robotics and Automation (ICRA), p. 4551-4556, Stockholm, Sweden, 2016
A. R. Geist, A. Hackbarth, E. Kreuzer, V. Rausch, M. Sankur and E. Solowjow
(See online at https://doi.org/10.1109/ICRA.2016.7487655) - Design and Adaptive Depth Control of a Micro Diving Agent. In IEEE Robotics and Automation Letters, 2(4): 1871-1877, 2017
W. Bessa, J. Lange, E. Kreuzer, M.-A. Pick, E. Solowjow
(See online at https://doi.org/10.1109/LRA.2017.2714142) - Embedded Spherical Localization for Micro Underwater Vehicles based on Attenuation of Electro-Magnetic Carrier Signals. Sensors, 17(5):959-981, 2017
D.-A. Duecker, A.R. Geist, M. Hengeler, E. Kreuzer, M.-A. Pick, V. Rausch, E. Solowjow
(See online at https://doi.org/10.3390/s17050959) - Low-Cost Monocular Localization with Active Markers for Micro Autonomous Underwater Vehicles. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), p. 4181-4188, Vancouver, Canada, 2017
A.D. Buchan, E. Solowjow, D-A. Duecker, E. Kreuzer
(See online at https://doi.org/10.1109/IROS.2017.8206279) - Learning Environmental Fields with Micro Underwater Vehicles: A Path Integral - Gaussian Markov Random Field Approach. Autonomous Robots, 42(4): 761- 780, 2018
E. Kreuzer, E. Solowjow
(See online at https://doi.org/10.1007/s10514-017-9685-2) - Micro Underwater Vehicle Hydrobatics: A Submerged Furuta Pendulum. In IEEE International Conference on Robotics and Automation (ICRA), Brisbane, Australia, 2018
D.-A. Duecker, A. Hackbarth, T. Johannink, E. Kreuzer, E. Solowjow
(See online at https://doi.org/10.1109/ICRA.2018.8461091)
