Model-Based Estimation of Uncertain Varying Geophysical Flows with a Swarm of Autonomous Underwater Vehicles
Sampling in marine environments is necessary and common practice to observe spreading of spills, monitor biological activities, to detect oceanographic events, or to analyze the water and sediment dynamics around offshore constructions. The term adaptive sampling is used to describe sampling missions where decisions are made autonomously while the mission is running. These decisions have to be thoughtfully implemented and defined a priori due to the uncertainty of the process that the mission shall be adapted to. Several studies have shown already, that instead of using a mobile sensor network with some smart local decision rules, it is much more efficient if a central predictor propagates a numerical model of the fluid domain and gives feedback to the mobile sensor nodes. In the last decade, the ensemble Kalman filter (EnKF) by Geir Evensen showed for meteorological data assimilation promising results compared to established variational approaches, but several issues mainly related to small ensemble sizes still exist. Publikationen- Hackbarth, Axel and Hedrick, J. Karl and Kreuzer, Edwin, Wieners, Christian: A Multi-Layered Potential Field Method for Multi-Agent Navigation, Searching and Tracking. In PAMM, Jg. 10Weinheim, dec 2010.
- A. Hackbarth and J.K. Hedrick and E. Kreuzer and E. Solowjow: A Nonlinear Estimator for Mobile Source Localization Applications. In Proc. of the 8th European Nonlinear Dynamics Conference, Vienna, Austria, 2014.
- Hackbarth, Axel and Kreuzer, Edwin and Schröder, Thorben: CFD in the Loop: Ensemble Kalman Filtering With Underwater Mobile Sensor Networks. In Ocean, Offshore and Arctic Engineering, ASME 2014 33rd International Conference on, jun 2014.
- Hackbarth, Axel and Kreuzer, Edwin and Gray, Andrew and Hedrick, J. Karl: Collaborative Control of Multiple AUVs for Improving the Estimation of Flow Field Dependent Variables. In IEEE/OES Autonomous Underwater Vehicles, Southampton, 2012.
- A. Hackbarth and J.K. Hedrick and E. Kreuzer and E. Solowjow: Localization of a Diffusive Source Using Rao-Blackwellized Particle Filtering. Robotics: Science and Systems Conference, Workshop on Autonomous Control, Adaptation, and Learning for Underwater Vehicles, Berkeley, CA, USA, 2014.
- Hackbarth, Axel and Gray, Andrew and Kreuzer, Edwin: Multi-Agent Motion Control of Autonomous Vehicles in 3D Flow Fields. In PAMM, Jg. 12Darmstadt, dec 2012.
- Hackbarth, Axel and Kreuzer, Edwin, Manzke, Manuel and Wöckner, Katja and Ulrich, Christian and Brunswig, Jörg: Source Localization and Tracking with a Swarm of Autonomous Underwater Vehicles. In 1st Interdisciplinary Workshop on Maritime Systems - Latest Results of Ph.D. Projects at TUHH, Hamburg, feb 2010.
- Bessa, Wallace M and Hackbarth, Axel and Kreuzer, Edwin and Radisch, Christian, Ecker, Horst and Alois, Steindl and Jakubek, Stefan: State and Parameter Estimation of an Electro-Hydraulic Servo System. In ENOC 2014 - Proceedings of 8th European Nonlinear Dynamics Conference, Vienna, 2014.
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