Papers
64
Total Citations
2,177
H-Index
20
About
Joonbum Bae is a prominent robotics researcher whose work spans human-robot interaction, actuator design, soft robotics, and bio-inspired systems. He is perhaps best known for his foundational contributions to rotary series elastic actuator (RSEA) technology, with his 2009 and 2011 papers on force-mode control and compact RSEA design accumulating over 750 citations combined — establishing him as a leading authority on safe, compliant actuation for human assistive and exoskeleton systems. His research on lower extremity exoskeletons and gait rehabilitation further demonstrates a sustained commitment to translating precision actuation into meaningful clinical and assistive applications. In recent years, Bae has expanded his focus into soft robotics, contributing a widely cited 2021 review of machine learning methods in the field (249 citations) and innovative work on hybrid grippers and self-sensing soft valves. His 2023 research on perceptive soft robots signals a forward-looking interest in integrating sensing and intelligence directly into soft robotic structures. Complementing these threads, his investigations into aquatic arthropod locomotion reflect a broader curiosity about bio-inspired design principles. Across more than a decade of research, Bae has built a coherent and influential body of work bridging mechanical design, control theory, and emerging soft robotic paradigms.
Research Focus
Key Achievements
Top Papers
- 1
- 2A Compact Rotary Series Elastic Actuator for Human Assistive Systems322 citations · 2011
- 3Review of machine learning methods in soft robotics249 citations · 2021
- 4A Hybrid Gripper With Soft Material and Rigid Structures126 citations · 2018
- 5
- 6A soft, self-sensing tensile valve for perceptive soft robots68 citations · 2023
- 7
- 8A compact rotary series elastic actuator for knee joint assistive system54 citations · 2010
- 9Gain-Adaptive Robust Backstepping Position Control of a BLDC Motor System41 citations · 2018
- 10A gait rehabilitation strategy inspired by an iterative learning algorithm39 citations · 2012