Matthew Baumann

Papers

Total Citations

204

H-Index

About

Matthew Baumann is a pioneering roboticist whose research lies at the intersection of computer vision, autonomous navigation, and semantic scene understanding. His most influential contribution is the development of **Curious George**, an integrated robotic platform that fuses real-time object recognition with web-sourced training data. The seminal paper, "Curious George: An attentive semantic robot" (2008), has garnered **167 citations**, establishing Baumann as a key figure in bringing semantic knowledge into physical robot systems. This work demonstrated a robot capable of autonomously querying online databases to identify and interact with objects in unstructured environments—a foundational step toward today’s internet-connected robots. Baumann also advanced practical manipulation with his work on **occlusion-free path planning** (2008), introducing a probabilistic roadmap algorithm that ensures an eye-in-hand camera maintains a clear view of a target while avoiding collisions. His 2010 follow-up paper further refined the Curious George system, showcasing state-of-the-art integration of perception, planning, and web-based learning. By bridging the gap between semantic reasoning and physical action, Baumann’s research continues to inspire students and engineers building robots that can learn from and navigate the real world.