Papers
15
Total Citations
192
H-Index
7
About
Youngbum Jun is a leading researcher in humanoid robotics, specializing in locomotion, manipulation, and autonomous task execution for disaster response and extreme environments. His most impactful work centers on enabling humanoid robots to operate reliably in unstructured, real-world settings—from rough terrains like grass, sand, and rocks to complex disaster scenarios. Jun was a key contributor to Team DRC-Hubo@UNLV in the 2015 DARPA Robotics Challenge Finals, where his team’s approach to robust hardware and software under degraded communication earned 49 citations. He developed continuous trajectory optimization for autonomous door opening (25 citations) and pioneered walking controllers for non-flat surfaces, advancing robots’ ability to traverse natural and damaged environments. His work on posture balance using state and disturbance-observer-based feedback (12 citations) and real-time ZMP preview control for obstacle avoidance (11 citations) further solidified his impact. Jun has also explored deep space humanoid robotics, inspired by the NASA Space Robotics Challenge, and addressed lift-and-carry tasks for non-rigid materials. With over 180 total citations, his contributions are foundational to making humanoids practical for hazardous, real-world missions.
Research Focus
Key Achievements
Top Papers
- 1
- 2DRC-hubo walking on rough terrains33 citations · 2014
- 3Continuous trajectory optimization for autonomous humanoid door opening25 citations · 2013
- 4Humanoid robots walking on grass, sands and rocks22 citations · 2013
- 5Planning complex physical tasks for disaster response with a humanoid robot15 citations · 2013
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- 7
- 8
- 9Towards tasking humanoids for lift-and-carry non-rigid material4 citations · 2017
- 10Team DRC-Hubo@UNLV in 2015 DARPA Robotics Challenge Finals3 citations · 2018