Robotics Research Earns IEEE King-Sun Fu Best Paper Award
ECE Postdoctoral Research Associate Alan Papalia and ECE/COS Assistant Professor David Rosen are recipients of the 2024 IEEE Transactions on Robotics King-Sun Fu Memorial Best Paper Award for their paper “Certifiably Correct Range-Aided SLAM.” This award recognizes the best paper published annually in the IEEE Transactions on Robotics.
This article originally appeared on Northeastern Global News. It was published by Cesareo Contreras. Main photo: Northeastern University postdoctoral research associate Alan Papalia tested his algorithm by riding in an autonomous surface vehicle on the Charles River. Courtesy photo
Northeastern researchers develop algorithm that could make underwater robots more economical
In the ocean sciences, robots provide views of the unexplored and can navigate environments not safely accessible to humans. Such dangerous settings make up the majority of the Earth’s oceans.
These robots come in all kinds of shapes, sizes, and dimensions, and are outfitted with various sensors and cameras used for capturing images, measuring structures, and figuring out where the robot is underwater.
Northeastern researchers Alan Papalia and David Rosen have developed an algorithm that improves the accuracy of a technology often used in underwater robotics—acoustic navigation, which uses acoustic sensors that emit, detect, and analyze sound waves to help robots understand their positioning in the water.
“You can use these acoustic sensors in a variety of ways: you can attach them to different robots and the robots can measure how far away they are from each other; or you can fix them to the environment (e.g., the seafloor) and measure how far away the robot is from the fixed sensors,” the researchers write in a summary of the report. “In a lot of ways, this is similar to how GPS works, which just estimates your position by measuring how far away you are from a set of satellites.”
While acoustic sensors are generally more accessible and cheaper to obtain than more expensive sensor systems, they are not as reliable in actually determining where a robot is at any given time in the water, explains Papalia, a Northeastern University postdoctoral research associate in the department of electrical and computer engineering and the lead author of the research.
One of the key issues with acoustic sensors is that “they don’t precisely tell you where you are; they just tell you how far away you are from another point,” Papalia explains.
“This means that even if the sensors are perfect (which they certainly are not), you only know that you are somewhere on a circle a fixed distance away,” he adds.
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