About

Byungjae Park is a leading researcher in autonomous mobile robotics, specializing in long-term localization, path planning, and human-robot interaction. His most influential work, "1-Day Learning, 1-Year Localization" (136 citations), introduces a Scan Context Image-based method that enables robust year-round LiDAR localization from just a single day of training—a breakthrough for real-world deployment. Park also pioneered the Co-Pilot Agent system (31 citations), a cooperative framework for vehicle/driver interaction and autonomous driving that prioritizes safety and traffic rule compliance. His foundational contributions to path planning include hierarchical roadmap representations (29 citations) and incremental construction methods (15 citations) that efficiently map indoor environments for mobile robots. More recently, Park has advanced real-time 3D multi-pedestrian detection and tracking using LiDAR point clouds (19 citations), addressing critical safety challenges for robots in crowded spaces. With over 260 total citations across his portfolio, Park’s work bridges theoretical innovation and practical application, from odometry calibration to logistics robots for Industry 4.0. His research continues to shape how autonomous systems perceive, navigate, and cooperate in dynamic environments.

Research Focus

Key Achievements

7
H-Index
10
Papers
269
Total Citations
27
Avg Citations/Paper
🏆 Most Cited Paper
1-Day Learning, 1-Year Localization: Long-Term LiDAR Localization Using Scan Context Image
136 citations · 2019
📈 Most Prolific Year: 2012 (3 Papers)
🤝 Key Collaborators: 21
🏛 Institutions: Electronics and Telecommunications Research Institute, Korea Post, Korea University of Technology and Education, Pohang University of Science and Technology

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago