Jaewon Jo

Papers

1

Total Citations

7

H-Index

1

About

Jaewon Jo is a robotics researcher whose work focuses on advancing the autonomy of mobile manipulators in complex, human-centric environments. His primary research areas include visual-based manipulation, autonomous navigation, and human-robot interaction, with a particular emphasis on enabling robots to operate seamlessly in multi-floor buildings. Jo’s most notable contribution is his pioneering approach to elevator button manipulation using a visual-based self-driving mobile manipulator, a critical capability for robots that cannot climb stairs. By integrating computer vision and precise manipulation, his 2022 paper provides an efficient solution for robots to independently navigate vertical spaces, a key step toward practical deployment in modern infrastructure. This work, which has garnered 7 citations, addresses a fundamental bottleneck in mobile robotics and has implications for service robots, logistics, and assistive technologies. Jo’s research stands out for its practical focus on real-world challenges, bridging the gap between laboratory prototypes and functional autonomous systems. His contributions are particularly valuable for students and researchers interested in embodied AI, sensorimotor control, and the integration of perception and action in unstructured environments.

Research Focus

Key Achievements

1
H-Index
1
Papers
7
Total Citations
7
Avg Citations/Paper
🏆 Most Cited Paper
An efficient approach for the elevator button manipulation using the visual-based self-driving mobile manipulator
7 citations · 2022
📈 Most Prolific Year: 2022 (1 Papers)
🤝 Key Collaborators: 1

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago