Field Estimation and Source Localization with Micro Autonomous Underwater Vehicles


Exploration of marine environments with autonomous robots has been a prominent topic in the last decade and will be expected to gain more importance in the future. In particular, the analysis and understanding of spatiotemporal dynamic processes and fields such as flow conditions, temperature, salinity, or oil concentration is at the core of many scientific disciplines and is becoming increasingly important for offshore engineering applications. Geoscience relies on the exploration of spatiotemporal fields to further the understanding of oceanic processes and climate phenomena. Engineering applications include flow field monitoring at offshore wind farms during installation, operations, and maintenance. Detection of hazardous sources, such as leaking dichloroethyl sulfide containers in the North Sea, is also of great importance. The increased efforts in deep sea mining promise further areas for deployment to localize hydrothermal vents and also to monitor the environmental impact. Lastly, many production steps in the process industry are concerned with liquids on a medium to large scale. However, monitoring these liquids with a high resolution in time and space proofs to be very difficult with current technology.


Next generation conceptual CAD rendering (upper left), working early prototype (upper right) and current version (bottom) of HippoCampus.

Project Description

We develop an AUV system with an environmental model in the loop. This model can either be a computational fluid dynamics (CFD) simulation or a probabilistic model such as Gaussian Randon Fields. This allows the modeling of realistic environmental dynamics and an estimation of sources (of heat and pollution). The mean and variance of the environmental model are fed back into the path planner for the AUVs. Task allocation and consensus algorithms decide how the team of vehicles navigates within the field to satisfy both, robustness and a fast mission execution.

Vehicle Hardware

The current underwater vehicle setup represents a very flexible and robust control platform. We use a Pixhawk board with a 168 MHz Cortex M4F CPU (256 KB RAM, 2 MB Flash) and onboard sensors (3D ACC / Gyro / MAG / Baro). PX4 is an independent, open-source, open-hardware project (BSD licensed) for mobile robotics applications. The PX4 platform runs NuttX, a small footprint real-time operating system (RTOS), which provides a POSIX-style environment. The PX4 middleware runs on top of the operating system and provides device drivers and a micro object request broker (uORB) for asynchronous communication. Our HippoCampus control stack is a custom, BSD licensed underwater vehicle control stack, providing remote controlled and fully autonomous operations for our underwater vehicle hardware.

Our GitHub repository 

The vehicle is easy to assemble and is made of off-the-shelf components, 3D printed parts and printed circuit boards. The quad-rotor layout makes the vehicle extremely agile and suitable for hydrobatic maneuvers.


Dipl.-Ing. Eugen Solowjow, M.-TecM (Contact)
Daniel-André Dücker, M.Sc.
Dipl.-Ing. Axel Hackbarth, MEngSt
Prof. Dr.-Ing. habil. Prof. E.h. Edwin Kreuzer



"We insist on building complete systems that exist in the real world so that we would not trick ourselves into skipping hard problems." Rodney Brooks, Artificial Intelligence Lab, MIT, 1989.



The birth:
Featured by IEEE Spectrum as one of the highlighted IROS15 videos:
ICRA16 contribution on acoustic localization for µAUVs:
HippoCampus 2.0:


Upcoming Events




Student Involvement

Current Students and Visiting Scholars

  • Johannink, Tobias: "Design of Underwater Vehicles", Student Research Assistant, 2017.
  • Rausch, Viktor: "Experimental Underwater Robotics", Student Research Assistant, 2017.
  • Geist, Rene: "Experimental Underwater Robotics", Student Research Assistant, 2017.
  • Rottmann, Nils: "Geometric Control of Micro Underwater Vehicles", Master Thesis, 2016.
  • Brinkmann, Gerrit: "Control and Learning with a Diving Agent", Master Thesis, 2016.
  • Maerker, Gunnar: "Parameter Estimation of Underwater Vehicles", Bachelor Thesis, 2017.
  • Hengeler, Michael (Bosch): "Control of an Underwater Robotic Manipulator on a Floating ROV", Master Thesis.
  • McPherson, David (UC Berkeley): "Path Integral Control of Underwater Robots", Visiting Scholar, 2017.
  • Chou, Fang-Chieh (UC Berkeley): "Guidance of Underwater Robots", Visiting Scholar, 2017.
  • Scheske, Alyssa (UC Berkeley): "Line-of-Sight Path-following of Underactuated Vehicles", Visiting Scholar, 2017.

Past Students Theses and Visiting Scholars

  • Rottmann, Nils: "Stochastic Processes for Environmental Modelling", Project Thesis, 2017
  • Lange, Johann: "Dive Robot Design and Control", Bachelor Thesis, 2016.
  • Buchan, Austin (UC Berkeley): "SLAM for Low-Cost Micro Robots", Visiting Scholar, 2016.
  • Lin, Hsien-Chung (UC Berkeley): "Data-Driven Contour Line Estimation of Environmental Fields", Visiting Scholar, 2016.
  • Kirchhoff, Max: "Controls for AUV Stabilization", Bachelor Thesis, 2016.
  • Hengeler, Michael: "Underwater Localization with RF Signals", Project Thesis, 2016.
  • Johannink, Tobias: "Konstruktion eines Unterwasserfahrzeugs für Schwarmanwendungen", Bachelor Thesis, 2016.
  • Marghany, Ahmed: "Ensemble Kalman Filtering and Lattice-Boltzman Method for Flow Estimation", Project Thesis, 2015.
  • Geist, Rene: "Hyperbolic Acoustic Localization of AUVs with EKF", Bachelor Thesis, 2015
  • Novelia, Alyssa (UC Berkeley): "Synchronization of Autonomous Agents on Uncertainty Manifolds", Visiting Scholar, 2015.
  • Sankur, Michael (UC Berkeley): "Acoustic Self-Localization for Marine Robotics", Visiting Scholar, 2015.
  • König, Malte: "Modellbildung und Entwurf eines Reglers zur Stabilisierung von Unterwasserfahrzeugen", Bachelor Thesis, 2015.
  • Hildebrandt, Andre: "Optimierung der Konstruktion und des Fertigungsprozesses eines autonomen Unterwasserfahrzeugs in Kleinserie", Bachelor Thesis, 2015.
  • Rausch, Viktor: "Akustische Lokalisierung",  Bachelor Thesis, 2014.
  • Garstka, Michael: "Modellbildung und Entwurf eines Reglers zur Trajektorienverfolgung von Unterwasserfahrzeugen", Bachelor Thesis, 2014.
  • Rottmann, Nils: "Entwicklung einer Tauchzelle zum experimentellen Nachweis der Orbitalbewegung von Wasserpartikeln unter Einfluss von Schwerewellen", Bachelor Thesis, 2014.
  • Penamora, Kim (UC Berkeley): "Design of Micro Underwater Vehicle and CFD Simulation of Rivers", Visiting Scholar, 2014.
  • Schröder, Thorben: "Datenassimilation für eine wärmegetriebene Strömung mittels Ensemble Kalman-Filterung", Master Thesis, 2013.
  • Syed, Shakil: "PID-Reglerentwurf und praktische Umsetzung zur Drehgeschwindigkeitssteuerung eines Unterwasserfahrzeugs", Bachelor Thesis, 2013.
  • Solowjow, Eugen: "A Bayesian Approach to Model-Based Localization of a Diffusive Source", Diploma Thesis, Vehicle Dynamics and Control Laboratory, Berkeley & Institute of Mechanics and Ocean Engineering, TUHH, Hamburg, 2012.
  • Dücker, Daniel: "Entwicklung und Simulation eines Multi-Kamera-Systems mit Datenfusion mittels Kalman-Filterung", Bachelor Thesis, 2012.
  • Uken, Simon: "Entwurf und praktische Umsetzung eines Prototypen für ein Miniatur-Unterwasserfahrzeug", Bachelor Thesis, 2012.
  • Luo, Xiaojing: "Identifikation von Wärmequellen in konvektiv getriebenen Strömungen", Diplomarbeit, Department Mathematik, UniHH & Institut für Mechanik und Meerestechnik, TUHH, Hamburg, 2011.
  • Gray, Andrew (UC Berkeley): Visiting Scholar, "Modelling and Control of Underwater Vehicles", Visiting Scholar, Summer 2010.