Yuli Friedman

Massachusetts Institute of Technology, BAE Systems (Sweden), BAE Systems (United States)

Papers

Total Citations

H-Index

About

Yuli Friedman is a roboticist whose work bridges the gap between autonomous machines and human-centered environments. His primary research areas include mobile manipulation, human-robot interaction, and vision-based object reacquisition—enabling robots to perceive and interact with objects in unstructured, real-world settings. Friedman’s most notable contribution is his work on a situational aware, voice-commandable robotic forklift designed to operate safely alongside people in outdoor industrial environments (47 citations). This research tackles the long-standing challenge of deploying heavy autonomous machinery in human workplaces, emphasizing safety and acceptance. He also pioneered a one-shot visual appearance learning algorithm (10 citations) that allows robots to robustly detect and reacquire specific objects after a single human-provided segmentation hint—even after extended spatial and temporal excursions. This work, extended through his papers on vision-based reacquisition for task-level control, enables intuitive human supervision via stylus gestures, allowing non-experts to guide robots in complex tasks. Friedman’s research directly advances the practicality of autonomous systems in logistics, manufacturing, and collaborative human-robot workspaces.