A r ti fi c i a l Intelligence Xavier Orr is approaching his 11th year as CEO of Advanced Navigation. The Sydney, Australia, company designs, develops and manufactures a diverse portfolio of inertial navigation and robotic systems, as well as underwater acoustic and RF technologies. For some time, the company has explored “a new approach to filtering based on artificial intelligence neural networking (ANN).” Orr began his two decades of examining AI/ neural networks during eight years studying mechatronic engineering and computer science, robotics and artificial intelligence at the University of Western Australia. INSIDE AI by ABE PECK, EXECUTIVE EDITOR Advanced Navigation: A Two-Decade Quest to Revolutionize Inertial Navigation S Comparison of GNSS and Spatial FOG system results. Error of distance traveled: 0.1% ince the Apollo Project of the 1960s targeted the moon, the venerable Kalman filter has of-fered estimates of unknown variables based on multiple measurements over time. But as GNSS jamming and spoofing technologies have challenged GNSS-only solutions, defense forces and others have sought alternatives for position information, adopting inertial navigation systems for trusted guidance and navigation applications. Xavier Orr, CEO of Advanced Navigation, has been developing alternatives to the Kalman filter for two decades. In the pro-cess, his mission has grown from grad-school theorizing into a company with a mission “to drive the autonomy revolu-tion with AI-powered systems delivering unparalleled capa-bilities and performance.” The company now has more than 1,000 clients and 35,000 sys-tems in the field. Herein lies a tale. IN THE BEGINNING “It was 2000,” Orr recalled about the roots of his AI od-yssey. “I think it was in my eighth year at university and I’d spent the last three years specifically focused on neural networks, which is probably the most predominant form of AI at the moment. Back then, there was no interest in it whatsoever. But through my work with it, I could see the potential applications and how we can re-ally benefit from it.” His research led him to encounter the Kalman filter, including some of its shortfalls. “At the end of 2008, I was doing control theory, where I was working a lot with the Kalman filter,” Orr said. “The Kalman filter really hasn’t had any major updates since the ’60s. It basically is linear-izing a physics model, and that’s always introducing error. I was thinking it was the perfect application for neural networks to try and solve this problem. So, I did my thesis on the application of neural net-working to inertial navigation.” The next year, Orr’s thesis was well-received, but his findings were too early to be implemented. “The technology wasn’t stable,” he recounted. “The results that were coming out were really good; we saw up to 10x performance versus a Kalman filter. But it just didn’t have the stability at that time.” So, the quest continued. “I spent about three more years working on it and managed to develop the layers to make it stable. The lion’s share of the work was in getting it stable.” BUILDING THE TECHNOLOGY In 2012, it was time to go forward with a company. “We’d done a lot of testing and verif ied for stabil-ity across all applications, and that was when we launched Advanced Navigation to commercialize the technology,” Orr reported. He joined forces All images courtesy of Advanced Navigation. inside 28 unmanned systems www.insideunmannedsystems.com August/September 2022