Gecko Robotics, a robotics company that helps organizations operate and maintain their physical assets, announced the official launch of the company’s Cantilever product. The solution integrates data from Gecko’s various robotic, fixed-sensor, and partner systems into a software platform that enables unparalleled analysis and decision-making about asset health. By bringing together data layers that were not previously possible, Cantilever drives important decisions for customers that increase uptime, decrease costs, and eliminate safety issues.
“Cantilever is designed to become the primary operating system for the physical world,” Jake Loosararian, CEO and Co-Founder of Gecko Robotics, said. “Every day, at hundreds of customer sites around the world, our robots are keeping power plants online, military assets ready, and factory doors open. That’s only possible because our robots and fixed sensor networks are collecting data at a quantity and quality that’s never been seen before. Cantilever begins with that unique data and combines it with the customer’s own data to create the first end-to-end solution, transforming decision making in the built world.”
Better Data Drives Better Outcomes
In the 21st century, most industries have been fundamentally changed by advances in robotics and smart sensor technology. However, the way asset health data on critical infrastructure is gathered has not changed in 50 years and is still primarily carried out in dangerous environments by hand. That leads to incorrect, incomplete, and insufficient data. Even the most sophisticated AI algorithms are not able to produce accurate results with insufficient data.
From Out-of-the-Box to Outcomes
The capabilities and applications of Cantilever address that problem for customers almost immediately. The Cantilever process begins with first principles. A combination of robots, drones, and fixed sensors collect data, which is combined with historical health records, design files, operational data, and other business metrics to create Cantilever data layers.
Those layers are processed through Cantilever’s AI-powered analysis platform, Data Systems, to determine key insights, like corrosion rate or remaining life. Those analyses are then imported into Cantilever’s software modules to empower customers to make targeted repairs, prioritize capital investments, and shift from reactive to predictive maintenance.
Cantilever is helping customers in the defense, manufacturing, and energy sectors solve some of their hardest problems. The U.S. Navy, an early adopter of Cantilever, uses it to combat the largest issue they face, ship availability. Commanding officers and maintenance teams generate and then act on repair plans in minutes – a process that previously took weeks or months to complete. Other industries are using Cantilever to optimize capital spending, extend the life of key assets, and prioritize maintenance spending to reduce costs, increase uptime and improve safety.
This is all pretty fuzzy and hand waving. It would be useful to supply some information about how the various scenarios work. My specific interest is what operating system is used, what programming languages are used and what software is used to collect sensor data and integrate it with running robots. Do you generate new code for each application or do you analyze the tasks to see which code can be reused across applications. Do you have APIs that other people can use to test and extend your systems. Is any of it open software and if so where is it published so that students and practitioners can look over your shoulders and make suggestions and generate code.