Hydrobatic Micro Robots for Field Exploration in Hazardous Environments

Motivation

Exploration of marine environments with autonomous robots has been a prominent topic in the last decade and is 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.

 

Our 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.

 

 

 

 

Project Description

We develop a 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.

Selected Publications

 

  • D.-A. Duecker, B. Mersch, R. C. Hochdahl, and E. Kreuzer.  Embedded Stochastic Field Exploration with Micro Diving Agents using Bayesian Optimization-Guided Tress-Search and GMRFs. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Prague (virtual), CZ, 2021.
  • D.-A. Duecker, C. Horst, and E. Kreuzer.  From Aerobatics to Hydrobatics: Embedded Agile Trajectory Planning for Micro Underwater Robots. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Prague (virtual), CZ, 2021.
  • 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. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Las Vegas, NV, USA, 2020.  (Winner of the IROS Best Entertainment and Amusement Paper Award)
  • S. Watson, D.-A. Duecker, and K. Groves. Localization of Unmanned Underwater Vehicles (UUVs) in Complex and Confined Environments: A Review. In Sensors, 2020, 20, 6203.
  • D.-A. Duecker, N. Bauschmann, T. Hansen, E. Kreuzer, and R. Seifried. HippoCampus X -- A Hydrobatic Open-source  Micro AUV for Confined Environments. 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. 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. 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.

 

Team

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 2020 in Las Vegas (virtually)!

 

Funding

This project is currently funded by

Videos

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: