UMD Researchers Show How Robots Can Measure Without Rulers

Babies and toddlers learn to judge size and distance by comparing objects to their own bodies, but robots, which “see” with sophisticated cameras and sensors, generally need precise measurements and calibrations to understand their environment.

Now, University of Maryland researchers are developing robotic sensing abilities that mimic biological systems, which ultimately could allow robots to navigate and manipulate objects without pre-programmed measurements.

Their work was recently published in npj Robotics, demonstrating how robots can “learn” from their own actions like pushing, jumping or reaching to better understand the world around them.

This method mirrors how insects or small rodents sense their surroundings, said Levi Burner Ph.D. ’25.

Burner, who earned his degree in electrical and computer engineering, said that he was initially driven to look for biologically inspired solutions by watching his dog, noticing how she naturally judged distances.

Burner worked with his academic advisers—Research Scientist Cornelia Fermüller of the Institute for Advanced Computer Studies (UMIACS) and computer science Professor Yiannis Aloimonos, who also has an appointment in UMIACS—to devise the solution; they tested it by having a robot determine on its own if it could fit through an opening using feedback from its own movements. In another experiment, a robot learned to jump across gaps by repeatedly moving back and forth, building an internal sense of gravity and distance.

Burner, who now works as a postdoctoral associate in the Intelligent Sensing Lab led by computer science Assistant Professor Chris Metzler and the Perception and Robotics Group led by Aloimonos and Fermüller, hopes that this work will influence future robotics developers. 

“I want to communicate and convince other robotics experts that this is a good way to build their systems,” he said. “I want to tell them, ‘No, don’t do that. We could do this instead.’ That’s my goal.”