Department of Electrical Engineering Assistant Professor Xiangnan Zhong is researching ways to make robots smarter. The UNT Engineering faculty member recently received a $175,000 Computer and Information Science and Engineering (CISE) Research Initiation Initiative (CRII) grant from the National Science Foundation, an award that recognizes up-and-coming faculty in the career pathway that is expected to lead to research independence and a subsequent stream of projects, discoveries, students and publications.

The grant will go towards addressing the challenges in machine learning for intelligent physical systems, such as robots, that interact with one another. One way Zhong intends to do this is by using machine learning methods to make it possible for the robots to self-navigate through a physical maze without running into walls, other robots or barriers in their path – ideally making them more efficient at problem-solving on their own.

“In a lot of ways, it’s like human learning. Sometimes, in our environment, we can have a teacher who can tell you what’s right or wrong, much like coding a robot to do,” said Zhong. “As we get older, we start to teach ourselves whether a decision is good or bad. That’s what we want to do with these robots; we want them to be self-learning and demonstrate intelligent control.”

The implications of Zhong’s research could eventually be applied to vehicles, homes and other technology where artificial intelligence is used.