Devoting Attention to the Details
Carter DiOrio (MSR '24) developed a newfound confidence in his technical knowledge while in the MSR program. Today he's showcasing that confidence at Caterpillar, the world's leading manufacturer of construction and mining equipment.
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Carter DiOrio (MSR '24) is part of the engineering rotational development program at Caterpillar, a leading manufacturer of construction and mining equipment. His work supports the company's autonomous mining solution, and the rotational program will prepare him to be an autonomy engineer at the company.
For now, he calls himself a developer at the company. He felt like he was a good developer when he earned his Bachelor of Science in computer science from Iowa State in 2023, but he sees a big difference from who he was then compared to who he is today.
That difference is thanks to Northwestern Engineering's Master of Science in Robotics (MSR) program.
"What MSR did is give me much more confidence in my technical knowledge outside of the pure programming aspects," DiOrio said. "It is significantly easier to raise issues I see and ask the right questions due to the breadth of technical knowledge covered in MSR. MSR covers so much content that I do not think a year of work would have provided the same level of technical expertise."
DiOrio displayed that technical expertise with his final MSR project. With a deep interest in image geometry and computer vision, DiOrio conducted an analysis of fiducial markers and camera calibration for his project.
Fiducial markers, such as an AprilTag, are objects that are used as a point of reference or measurement in an image.
"I was excited to work on a project that cared deeply about accuracy," he said. "Not just about accuracy of measurements, but the detail-oriented work — the step up from 'how do we take this measurement' to 'what is the most correct way to take this measurement' and discussing the tiny details."
Those tiny details were challenging.
Heading into the project, DiOrio figured the hardest part would be coming up with ways to improve fiducial markers. Instead, measuring the baseline and any improvements proved to be most difficult. But he persisted.
To the best of DiOrio's knowledge, there are no papers or articles that mirror his attempt to empirically measure the accuracy of fiducial markers.
"All known papers judge the accuracy of the marker via synthetic data and simulations where you know the exact location of the virtual marker and virtual camera," he said. "We had a strong desire to verify the results empirically and spent a significant amount of time rediscovering why it is extremely difficult to do so."
Understanding the importance of careful measurement was one of DiOrio's biggest takeaways from the project.
MSR taught him how to be a more confident developer — and a more confident learner overall.
"I do not see complicated robotics concepts as impossibly out of reach anymore," he said. "Why? Because I had to tackle some of them throughout the program."
MSR also showed DiOrio a valuable lesson that he now applies to his work at Caterpillar. It's a realization he shares with anyone interested in robotics.
"Robotics and artificial intelligence can be flashing and exciting. That makes you want to jump straight in and work on the 'cool' aspects," he said. "But the fundamental theories, physics, and math behind all of it, while not immediately as impressive, are tremendously helpful to understand."