About

Hyejeong Ryu’s research lies at the intersection of mobile robotics, autonomous navigation, and intelligent path planning, with a focus on enabling robots to operate efficiently in large, complex, and unknown environments. Her major contributions include pioneering hierarchical path-planning frameworks that combine skeletonization with the RRT* algorithm, significantly improving computational efficiency and path quality for mobile robots. Her work on online complete coverage path planning using two-way proximity search and local map-based exploration with breadth-first search has advanced the state of the art in autonomous exploration. Ryu’s most cited papers—each garnering over 40 citations—demonstrate the lasting impact of her methods on the robotics community. She also introduced frontier-graph structures for graph search-based exploration, allowing robots to systematically reduce unknown areas while managing local grid maps. Her recent work on waypoint visibility-based target planners continues to push boundaries in hierarchical path planning for dynamic environments. With a consistent record of publications from 2013 to 2025, Ryu has established herself as a key contributor to practical, scalable solutions for mobile robot navigation and exploration.

Research Focus

Key Achievements

6
H-Index
8
Papers
137
Total Citations
17
Avg Citations/Paper
🏆 Most Cited Paper
Online complete coverage path planning using two-way proximity search
42 citations · 2017
📈 Most Prolific Year: 2020 (2 Papers)
🤝 Key Collaborators: 6
🏛 Institutions: Kangwon National University, Japan Advanced Institute of Science and Technology, Pohang University of Science and Technology

Top Papers

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

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago