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About

Andrew Dornbush is a robotics researcher whose work focuses on enabling autonomous systems to operate effectively in complex, unstructured environments. His key research areas include motion planning, autonomous exploration, and mobile manipulation. Dornbush made significant contributions to the development of anytime incremental planning algorithms, such as his work on E-Graphs (2013, 15 citations), which allow robots to find efficient, cost-minimizing motion paths quickly—a critical capability for real-world operation among people. He also advanced multi-robot exploration with his work on the air-ground robotic system (2015, 24 citations), demonstrating how teams of robots can autonomously map and navigate unknown spaces. More recently, Dornbush has focused on fieldable human-scale mobile manipulation through the RoMan project (2020, 6 citations), aiming to create robotic teammates capable of performing dangerous tasks. His framework for robot truck unloading (2020, 2 citations) showcases his ability to integrate planning, learning, and reasoning for complex industrial applications. With a career dedicated to bridging the gap between theoretical planning and practical deployment, Dornbush’s work continues to push the boundaries of autonomous robotics in challenging real-world settings.