Papers
7
Total Citations
247
H-Index
6
About
Sunggoo Jung is a leading roboticist specializing in autonomous navigation in extreme, unstructured environments. His most impactful work centers on the development of the NeBula autonomy framework, which was instrumental in TEAM CoSTAR’s victory in Phase II of the DARPA Subterranean Challenge. This system, detailed in papers with over 150 combined citations, integrates novel algorithms for perception, planning, and control, enabling robots to explore unknown tunnels and urban ruins without GPS or prior maps. Jung also made significant contributions to high-speed aerial autonomy, winning the 2016 IROS Autonomous Drone Racing Challenge with a direct visual servoing framework. His research further addresses critical challenges in collision-free local planning and semantic-based navigation under perceptual uncertainty, ensuring safe and efficient traversal of mobility-stressing terrain. Jung’s work on multi-UAV mission management for the MBZIRC 2017 competition demonstrates his ability to scale complex aerial logistics. Through his leadership in developing robust, lightweight autonomy for confined spaces, Jung has established himself as a key figure in pushing the boundaries of field robotics, enabling resilient exploration in the most challenging environments on Earth.
Research Focus
Key Achievements
Top Papers
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- 5Collision‐free local planner for unknown subterranean navigation10 citations · 2021
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