Junhee Park

Electronics and Telecommunications Research Institute

Papers

Total Citations

H-Index

About

Junhee Park is a researcher at the forefront of autonomous robotics and lifelong machine learning. His work is defined by a dual focus: enabling robust real-world robot autonomy and advancing the algorithms that allow AI systems to learn continuously without forgetting. Park’s most impactful contribution is his comprehensive 2020 study on autonomous mobile robot navigation, which has garnered 21 citations. This work provides a vital, end-to-end framework for indoor navigation, tackling the complex pipeline from sensor input and mapping to localization and motion planning—a crucial resource for researchers building complete robotic systems. Complementing this, his forward-looking survey on continual learning (5 citations) systematically categorizes state-of-the-art approaches and benchmarks, offering a clear roadmap for a field essential to deploying AI in dynamic environments. By bridging the gap between practical robot navigation and the theoretical challenges of lifelong learning, Park is helping to shape a future where machines can both move and adapt with increasing sophistication.