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Xuesu Xiao oozes enthusiasm when he talks about his off-road robotics testbed in ��������’s new Fuse building at Mason Square. 

“I'm extremely excited about this because it’s an only-of-its-kind thing on the planet. Nowhere else has such abilities. Off-road mobility and autonomy is a very difficult area to study and investigate because you need to have supporting facilities, you need to have off-road terrain, and you need to have the vehicles. We have all of that,” said the computer science assistant professor.

Xiao is a roboticist who develops algorithms to make robots not only capable, but also intelligent. His goal is that robots will someday work in the real world; humans will stand aside while robots go places that humans don't want to—or simply cannot—go.

“We want them to go to a forest to search for a victim who is lost in the woods,” he said. “We have a proposal in review right now to build robot firefighters. We want them in the field, doing things like scientific exploration in the South Pole.” 

Presently, autonomous driving generally involves road networks with traffic lights and lane markings. Xiao’s research focuses on motion planning: using machine learning to determine a series of movements to get a robot from a starting point to a goal while avoiding obstacles.

“That is where AI comes into place,” said Xiao. “We want robots not only to be programmed to do things, but also to learn from themselves, from the humans around them, and from each other.” 

The testbed where Xiao and students put their robots through their paces is about 700 square feet of rocks and faux vegetation. Xiao is intimately familiar with the space, having placed most of the rocks himself. “I'm very, very proud of this testbed, which has more than seven tons of rocks. I took five of our students of seven or eight trips to the landscaping store. It was an exhausting week!”

The terrain is rugged, designed to represent a real-life situation. “Off-road environments may get the robot stuck because the terrain may be deformable—changing shape under weight,” Xiao said. “Off-road terrain may make the robot roll over because, if there are a lot of rocks, they may need to crawl over them. You don't want the vehicle to roll over on top of those things. Successfully maneuvering this terrain is a very, very big thrust of our lab.”

The testbed is built to a one-tenth scale. A motion-capture system of eight cameras (soon to be upgraded to 16) surveils the entire terrain. Xiao says that his team knows exactly how the vehicles are moving with six-degrees-of-freedom tracking. 

The year has been busy for Xiao, who in 2025 won the university-wide Presidential Award for Faculty Excellence and the College of Engineering and Computing’s Excellence in Research Award. He is also George Mason’s sole nominee for the Rising Star Outstanding Faculty Award by the State Council of Higher Education for Virginia.  

While he appreciates that recognition, Xiao isn’t one to rest on his laurels. He is particularly excited about what’s next in the lab: He just ordered an autonomous Polaris “side-by-side”—a $300,000 autonomous off-road vehicle that can hold two people. He also talked about a capability that allows the testbed to be used far from George Mason. 

“I was at a conference in Korea, and we opened our testbed to the entire world by using a web interface. So, the attendees of the Conference on Robot Learning in Korea could drive our robots in Fuse in Arlington, Virginia.” 

With robots at George Mason taking commands from the other side of the globe, Xiao is showing that in robotics, there are no borders—only new frontiers to explore.