Total to design robots for autonomous industrial site inspections

June 13, 2018 // By Julien Happich
Total to design robots for autonomous industrial site inspections
Following the completion of the ARGOS Challenge it launched back in 2013 in partnership with the French national research agency (ANR), gas and oil extraction group Total is nearing its goal to have autonomous robots perform routine inspection tasks at its extraction sites and refineries.

Ultimately, the company wants such rugged autonomous robots to go everywhere operators can and carry out inspections, read and record measurements, but also in area where human operators would be at risk, reducing their exposure to potentially dangerous situations. By automating routine inspection tasks the robots would help the company streamline the operation of its onshore and offshore facilities, optimising their efficiency while cutting costs.

Here, ARGOS stands for Autonomous Robot for Gas & Oil Sites. In 2014, Total selected five teams out of 30 projects submissions from 15 different countries, and assigned to each one of them a global budget of up to €600,000 to conduct their research and development work within a three-year period.

Then from June 2015 to March 2017, the five teams from Austria and Germany (ARGONAUTS), Spain and Portugal (FOXIRIS), France (VIKINGS), Japan (AIR-K) and Switzerland (LIO) were able to test their prototypes in Lacq (South West France) on a competition site representative of Total's facilities and operating conditions.

The five robot prototypes that competed in the ARGOS challenge.

Among the specifications set by Total, the winning robot had to be able to navigate (move over unknown obstacles, climb stairs, detect operators) and perform inspections autonomously in a potentially explosive atmosphere (ATEX standard) to deliver reliable information and analyses.

The robots were also tested for critical case scenarios such as malfunctions, emergency shut-downs, low-battery, but also for their capability to operate in difficult situation (loss of WiFi connection), detect anomalies at inspection points or monitor their environment through sound analysis (including sound-based predictive maintenance for operating pumps).

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