With every push, the robot is learning to recognize the object through a new system developed by a team of UT Dallas computer scientists. Previous approaches have relied on a single push or grasp by the robot to “learn” the object. “To the best of our knowledge, this is the first system that leverages long-term robot interaction for object segmentation,” Xiang said. Ninad Khargonkar, a computer science doctoral student, said working on the project has helped him improve the algorithm that helps the robot make decisions. Other UTD authors of the paper included computer science graduate student Yangxiao Lu; computer science seniors Zesheng Xu and Charles Averill; Kamalesh Palanisamy MS’23; Dr. Yunhui Guo, assistant professor of computer science; and Dr. Nicholas Ruozzi, associate professor of computer science.