Robohub.org
 

Robots on drilling platforms: Austrian-German consortium wins international competition


by
22 May 2017



share this:

Photo credit: taurob GmbH and TU Darmstadt

Last week taurob, together with research partner TU Darmstadt, was announced the winner of the ARGOS Challenge, powered by Oil & Gas giant Total S.A.

In a three-year competition, five international teams competed to develop a robot for routine-, inspection- and emergency operations on oil & gas sites. Frequently, gas leaks on oil drilling rigs can cause an increased risk to safety and the environment.

The acronym ARGOS stands for Autonomous Robot for Gas and Oil Sites, which suggests that the robot independently performs assigned tasks. If necessary, an operator can intervene at any time via a satellite-based connection from land and take control of the robot.

Photo credit: taurob GmbH and TU Darmstadt

The robot, developed by taurob GmbH together with TU Darmstadt, can read pointer instruments, fill level displays as well as valve positions using cameras and laser scanners. It can measure temperatures and gas concentrations, detect abnormal noises, obstacles and people around them, and safely manoeuvre on wet stairs. Adverse environmental conditions such as heavy rain, extreme temperatures and wind speeds do not pose a problem.

“Our robot is also the first fully automated inspection robot in the world that can be used safely in a potentially explosive atmosphere,” says Dr Lukas Silberbauer, who together with his colleague Matthias Biegl, founded the company taurob in 2010. The reason behind it, the robot is already fully ATEX certified so that it doesn’t trigger an explosion while operating in potentially explosive gases.

The Austrian company could capitalize on their knowledge obtaining this certification during their first project: a robot for firefighters.

“When we heard about Total’s contest, we immediately realized that this would be a great opportunity for us,” says Matthias Biegl.

Total has announced that it will use the new robots starting from 2020 on its oil drilling rigs.

The project was supported by FFG (Österreichische Forschungsförderungsgesellschaft) in the context of EUROSTARS (Co-financed by the EU).

Team ARGONAUTS. Credit: Argos Challenge



tags:


Robohub Editors

            AUAI is supported by:



Subscribe to Robohub newsletter on substack



Related posts :

ACM SIGAI Autonomous Agents Award 2027 open for nominations

  20 Oct 2026
Nominations are solicited for the 2027 ACM SIGAI Autonomous Agents Research Award.

Powered by muscle cells, a paper-thin robot swims through watery maze

  19 Oct 2026
MIT engineers’ new aquabot offers a way to design small, efficient “biohybrid” robots.

Robot Talk Episode 166 – Evolving robot bodies and brains, with Rika Antonova

  16 Oct 2026
In the latest episode of the Robot Talk podcast, Claire chatted to Rika Antonova from the University of Cambridge about using artificial intelligence to develop complimentary robot hardware and algorithms.

Humanoid robots can sprint and box – but the real test is doing the laundry

  12 Oct 2026
No robot system can yet reliably handle the whole laundry process. Even folding remains a challenge.

Robot Talk Episode 165 – Robots behind the research, with Kushant Patel

  09 Oct 2026
In the latest episode of the Robot Talk podcast, Claire chatted to Kushant Patel from Brookhaven National Laboratory about robots that work in scientific facilities, such as particle accelerators.

What three days building a robot taught me

and   07 Oct 2026
The brief sounded simple: build a small autonomous robot, then make it survive increasingly difficult mazes. Simple... right? Until you actually have to build one.

Research could guide the future design of social robots

  05 Oct 2026
Giving robot companions animal-like or anime-style faces and voices could maximise their emotional appeal to users, according to new research which could help guide the growing field of social robotics.


↑


AUAI is supported by:







Subscribe to Robohub newsletter on substack




 















©2026.05 - Association for the Understanding of Artificial Intelligence