Micro Underwater Robotics

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

Our GitHub AprilTag-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.

HOOU-Courses

https://learn.hoou.de/blocks/course_overview_page/course.php?id=738

https://learn.hoou.de/blocks/course_overview_page/course.php?id=930

Upcoming Events

Meet us at ICRA 2025 in Atlanta!

Contact

Alumni

Thies Lennart Alff, M. Sc.
Dr.-Ing. Eugen Solowjow
Dipl.-Ing. Axel Hackbarth
Prof. Dr.-Ing. habil. Prof. E.h. Edwin Kreuzer