Autonomous systems are becoming more prevalent in a variety of industries and applications, and Xiangru Xu believes this trend will continue growing rapidly.
Think self-driving cars, drones, warehouse robots, robot vacuum cleaners, Mars rovers and robots for research and rescue operations.
“But there are still a lot of technological challenges about safety and human interaction that need to be addressed before people are confident and comfortable about having more autonomous systems around us,” says Xu, who joined the Department of Mechanical Engineering as an assistant professor in July 2019. “For example, we need to ensure the system will behave safely in a changing and complex environment, and that it will be able to operate even if certain components fail.”
Drawing on his expertise in feedback control theory, Xu is tackling many of these challenges by developing better control algorithms for autonomous systems that provide safety guarantees while maintaining those systems’ performance.
Research on autonomous systems involves sensing (knowing about the environment and its own state), reasoning (making logical decisions), and acting (producing motions). Xu’s research in the area of feedback control theory falls in the “acting” category, which aims to regulate the behavior, or dynamics, of the “body” of a system in the presence of noise, disturbance and uncertainty.
“I believe feedback control theory will play a key role in addressing many challenging problems in autonomous systems,” he says. “The ultimate goal is to make autonomous systems think independently, learn adaptively and act intelligently.”
His research involves deriving fundamental theorems that can be implemented in various dynamic systems to achieve the desired performance.
Xu earned his bachelor’s degree in applied mathematics from Beijing Normal University in 2009. After earning his PhD in control and modeling from the Chinese Academy of Sciences in 2014, Xu was a postdoctoral researcher in the Department of Electrical Engineering and Computer Science at the University of Michigan. While at Michigan, Xu and his collaborators proposed a convex optimization-based control design framework that’s useful for advancing the safety control of automotive systems. Their work garnered a best paper award from the IEEE Robotics and Automation Society.
Prior to joining UW-Madison, he conducted postdoctoral research at the University of Washington-Seattle’s Department of Aeronautics and Astronautics, where his control research enhanced drone safety.
He says UW-Madison’s highly collaborative environment attracted him to the university.
“I found there is basically no barrier for interdisciplinary research collaboration at UW-Madison and people here are very friendly,” he says.
Xu plans to continue work on the theoretical foundation of optimization-based control in order to push the performance and enhance the safety of autonomous systems. Although his research has been focused on theory, at UW-Madison he wants to bridge the gap between feedback control theory and its engineering applications.
“I foresee collaboration with faculty across the UW-Madison campus whose research also benefits from autonomous systems, such as researchers working in control theory, robotics, computer vision, machine learning, geoscience and agriculture,” he says.
Xu plans to build a research lab that includes a 300-square-foot drone flying zone with a motion capture system. Xu and students in his lab are also building several robots themselves, including drones and scaled cars.
“With the drone and scaled car testbeds, my lab can develop and test advanced control algorithms for autonomous systems,” he says.
Xu envisions his lab’s drone flying equipment not only complementing the drone space in the college’s Makerspace but also being useful for educating students on the control of autonomous systems. For example, he says the drones could be used in Mechanical Engineering Assistant Professor Peter Adamczyk’s Introduction to Robotics (ME439) course, or in other robotic control courses in the future.