In the IMPACT system, robot reasons on its own without training that a plastic bottle, harmless alone, becomes unsafe to touch the moment it’s sitting next to a glass one. (Image // Midjourney)
Most robots are trained to avoid touching anything at all. Reach into a cluttered fridge, and a standard robot will freeze rather than risk knocking something over, even if all that’s in its way is an empty water bottle.
A new system built by two USC Viterbi School of Engineering and USC Stevens School of Computing and AI graduate students from the Thomas Lord Department of Computer Science aims to fix that, by teaching robots to make judgment calls and act on them with precision instead of playing it safe by default.
Called IMPACT, it’s the product of over two years of work by 2025 master’s in computer science (artificial intelligence) graduate Karan Owalekar and second-year computer science PhD student Yiyang Ling, and which was recently accepted into the 2026 IEEE International Conference on Robotics and Automation (ICRA). — one of the top venues in AI research.
The work was co-supervised by Daniel Seita, an assistant professor of computer science and the director of the Sensing, Learning, and Understanding for Robotic Manipulation (SLURM) lab at the Thomas Lord Department of Computer Science. Another supervisor was Erdem Biyik, an assistant professor of computer science and electrical and computer engineering at the Thomas Lord Department of Computer Science and the Ming Hsieh Department of Electrical and Computer Engineering.
