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 (left) and current version (right) of the HippoCampus µAUV.


Project Description

We develop an  micro AUV exploration framework 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 Random 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.

Underwater Robot Platform

The current underwater vehicle setup represents a very flexible and robust control platform. The computing is shared among  an of off-the shelf single-board computer (currently Raspberry Pi 4) which processes high-level tasks such as path planning. and a fligth control unit (FCU) handling the low-level attitude of the vehicle. For flight controller we use a Pixracer board which comes with a 180MHz Cortex M4F CPU (256 KB RAM, 2 MB Flash) and multiple onboard sensors (3D ACC / Gyro / MAG / Baro). The FCU runs the  PX4 firmware 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 Firmware-Repository 

Our GitHub RF-Localization-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.

Research Philosophy

"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.


Selected Publications


  • D.-A. Duecker, N. Bauschmann, T. Hansen, E. Kreuzer, and R. Seifried. Towards Micro Robot Hydrobatics: Vision-based Guidance, Navigation, and Control for Agile Underwater Vehicles. (accepted at) IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Las Vegas, NV, USA, 2020.
  • D.-A. Duecker, N. Bauschmann, T. Hansen, E. Kreuzer, and R. Seifried. HippoCampus X -- A Hydrobatic Open-source  Micro AUV for Confined Environments. (accepted at) IEEE/OES Autonomous Undewater Vehicles (AUV) Symposium, St. Johns, Canada, 2020.
  • D.-A. Duecker, F. Steinmetz, E. Kreuzer, and C. Renner. Micro AUV Localization for Agile Navigation with Low-cost Acoustic Modems. (accepted at) IEEE/OES Autonomous Undewater Vehicles (AUV) Symposium, St. Johns, Canada, 2020.
  • D.-A. Duecker, T. Hansen, and E. Kreuzer. RGB-D Camera-based Navigation for Autonomous Underwater Inspection using Low-cost Micro AUVs. (accepted at) IEEE/OES Autonomous Undewater Vehicles (AUV) Symposium, St. Johns, Canada, 2020.
  • D.-A. Duecker, K. Eusemann, and E. Kreuzer. Towards an Open-Source Micro Robot Oceanarium: A Low-Cost, Modular and Mobile Underwater Motion-Capture System. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Macau, China, 2019.
  • D.-A. Duecker, T. Johannink, E. Kreuzer, V. Rausch, and E. Solowjow. An Integrated Approach to Navigation and Control in Micro Underwater Robotics using Radio-Frequeny Localization. In IEEE International Conference on Robotics and Automation (ICRA), Montreal, Canada, 2019.
  • D.-A. Duecker, A.R. Geist,  E. Kreuzer, and E. Solowjow. Learning Environmental Field Exploration with Computationally Constrained Underwater Robots: Gaussian Processes meet Stochastic Optimal Control. In Sensors, 2019.
  • D.-A. Duecker, A. Hackbarth, T. Johannink, E. Kreuzer, and E. Solowjow. Micro Underwater Vehicle Hydrobatics: A Submerged Furuta Pendulum. In IEEE International Conference on Robotics and Automation (ICRA), Brisbane, Australia, 2018.
  • G. Brinkmann, W.M. Bessa, D.-A. Duecker, E. Kreuzer, and E. Solowjow. Reinforcement Learning of Depth Stabilization with a Micro Diving Agent. In IEEE International Conference on Robotics and Automation (ICRA), Brisbane, Australia, 2018.
  • E. Kreuzer and E. Solowjow. Learning Environmental Fields with Micro Underwater Vehicles: A Path Integral - Gaussian Markov Random Field Approach. Autonomous Robots, 2017.
  • A.D. Buchan, E. Solowjow, D.-A. Duecker, and E. Kreuzer. Low-Cost Monocular Localization with Active Markers for Micro Autonomous Underwater Vehicles. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Vancouver, Canada, 2017.
  • D.-A. Duecker, A.R. Geist, M. Hengeler, E. Kreuzer, M.-A. Pick, V. Rausch, E. Solowjow. Embedded Spherical Localization for Micro Underwater Vehicles based on Attenuation of Electro-Magnetic Carrier Signals. In Sensors, 2017.
  • A. R. Geist, A. Hackbarth, E. Kreuzer, V. Rausch, M. Sankur and E. Solowjow. Towards a Hyperbolic Acoustic One-Way Localization System for Underwater Swarm Robotics. In IEEE International Conference on Robotics and Automation (ICRA), Stockholm, Sweden, 2016.
  • A. Hackbarth, E. Kreuzer, and E. Solowjow. HippoCampus: A Micro Underwater Vehicle for Swarm Applications. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Hamburg, Germany, 2015.



Daniel-André Dücker, M.Sc. (Contact)

Dipl.-Ing. Eugen Solowjow, M.-TecM
Dipl.-Ing. Axel Hackbarth, MEngSt
Prof. Dr.-Ing. habil. Prof. E.h. Edwin Kreuzer

Upcoming Events

  Meet us at

  • IROS 2019 in Macau, China!



This project is currently funded by


ICRA 2018 contribution on control and design of µAUVs:
Featured by IEEE Spectrum as one of the highlighted IROS15 videos:
ICRA16 contribution on acoustic localization for µAUVs:
HippoCampus 2.0:
The birth of the first HippoCampus µAUV:

Student Involvement

A key component of this project is the strong student involvement which takes place at all development stages.

Current Students and Visiting Scholars

  • Hansen, Tim "A Framework for Aqua-Culture Monitoring Using Low-Cost Micro Underwater Robots ", Master Thesis, 2020.
  • Horst, Christian "Agile Obstacle Avoidance with Autonomous Micro Underwater Robots", Master Thesis, 2020.
  • Maroofi, Sean "Acoustic Localization for agile Micro Underwater Robots", Bachelor Thesis, 2020.
  • Alff, Lennart "Communication and control for a Multi-Agent Network of Micro Underwater Robots", Project Thesis, 2020.
  • Flehmke, Malte "Machine Learning-based Strategies for Parameter Identification in Micro Underwater Robotics", Project Thesis, 2020.
  • Mersch, Benedikt "Field Exploration with micro Underwater Robots: Theorie and Experiment", Master Thesis, 2019.
  • Büsch, Lukas: "Cooperative Localization for Underwater and Surface Robots Hazardous Envrionments", Bachelor Thesis, 2019.
  • Sartorti, Roman: "Multi-Vehicle Tracking using a Modular Underwater Camera System", Bachelor Thesis, 2019.
  • Perez,  Natalia (UC Berkeley): "Modelling, Simulation, and Control of Micro Underwater Robots", Visiting Scholar, 2019.
  • Chen,  Sunny (UC Berkeley): "Convolutional Neural Networks for Underwater Object Detection", Visiting Scholar, 2019
  • Phillips, Patrick (U Rochester): "Stochastic Path Planning for Environmental Field Exploration", Visiting Scholar, 2019
  • Mallinger, Miles : "Development of an external modular Tracking System for Underwater Vehicles", Student Research Assistant, 2019.
  • Bauschmann, Nathalie: "Navigation and Control for agile micro Autonomous Underwater Vehicles", Student Research Assistant, 2019.
  • Hochdahl, René: "Cooperative Control for a Swarm of Micro Diving Agents", Bachelor Thesis, 2019.
  • Eusemann, Kevin: "A Modular Multi-Vehicle Underwater Tracking System using Monocular Cameras and Kalman Filtering Techniques", Bachelor Thesis, 2019


Past Student Projects, Theses, and Visiting Scholars

  • Bauschmann, Nathalie: "Embedded Vision-Based Localization for Underwater Robot Control", Bachelor Thesis, 2018.
  • Grunsfeld, Mace (UC Berkeley): "Micro Dive Agents for Underwater Swarm Applications", Visiting Scholar, 2018.
  • Timmermann, Nils: "Cooperative Control for Micro Autonomous Underwater Vehicles", Master Thesis, 2018.
  • Hoffmeister, Jonas: "Methods for RF-Antenna misalignement compensation using an extended Kalman filter", Bachelor Thesis, 2018.
  • Ertekin, Mahmut: "Yaw Estimation based on RF-signal attenuation by means of Particale Filtering", Bachelor Thesis, 2018.
  • Maerker, Gunnar: "Model Identification for Micro Underwater Vehicles", Student Research Assistant, 2018.
  • Johannink, Tobias: "Design and Control of Underwater Vehicles", Student Research Assistant, 2018.
  • Rausch, Viktor: "Localization and Position Control for Underwater Robots", Master Thesis, 2018.
  • Geist, Rene: "Stochastic Field Estimation with Underwater Robots", Master Thesis, 2018.
  • Kahlefendt, Chris (U Western Australia): "Implementation and Evaluation of Monocular SLAM for an Underwater Robot", Master Thesis 2018
  • Rottmann, Nils: "Geometric Control and Stochastic Trajectory Planning for Micro Underwater Vehicles", Master Thesis, 2017.
  • Johannink, Tobias,: "Design and Control of a Submerged Furuta Pendulum with an Underwater Robot", Project Thesis, 2017.
  • 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.