Papers

17

Total Citations

225

H-Index

8

About

Jaerock Kwon is a robotics and autonomous systems researcher whose work has made meaningful contributions to mobile robot navigation, indoor localization, and autonomous vehicle development. His research is particularly distinguished by its emphasis on cost-effective, practical solutions — a philosophy evident across his most influential publications. Kwon's early work focused on indoor robot navigation, leveraging ultrasonic sensors, QR-code-based localization, and smartphone technology to create reliable, low-cost alternatives to expensive proprietary systems. His 2014 paper on an autonomous tour guide robot, which has garnered 46 citations, exemplifies this approach, demonstrating how affordable hardware can achieve robust real-world performance. Complementary work on QR-code ceiling-mounted landmarks and particle filter localization (each earning 32 citations) further cemented his reputation in the indoor robotics space. Kwon subsequently extended his expertise to autonomous vehicles, developing software-in-the-loop simulation frameworks that support safer, more accessible autonomous driving research — work that has attracted growing attention from the broader community. He has also shown a commitment to engineering education, exploring how robots and smartphones can inspire the next generation of engineers. Across his career, Kwon's research reflects a consistent dedication to making advanced robotics accessible, practical, and impactful.

Research Focus

Key Achievements

8
H-Index
17
Papers
225
Total Citations
13
Avg Citations/Paper
🏆 Most Cited Paper
Autonomous tour guide robot by using ultrasonic range sensors and QR code recognition in indoor environment
46 citations · 2014
📈 Most Prolific Year: 2014 (3 Papers)
🤝 Key Collaborators: 20
🏛 Institutions: Kettering University, Yunnan University, University of Michigan–Dearborn

Top Papers

  1. 1
  2. 2
  3. 3
  4. 4
  5. 5
  6. 6
  7. 7
  8. 8
  9. 9
  10. 10

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago