Dongsuk Jeon
Papers
1
Total Citations
37
H-Index
1
About
Dongsuk Jeon is a researcher whose work lies at the intersection of reinforcement learning, robotics, and intelligent navigation. His key contributions focus on developing curriculum learning strategies that enable autonomous agents to progressively master complex tasks—starting from simple collision avoidance and advancing to navigating among movable obstacles in dynamic environments. His 2023 paper, "Curriculum Reinforcement Learning From Avoiding Collisions to Navigating Among Movable Obstacles in Diverse Environments," has already garnered 37 citations, reflecting its timely impact on the field. Jeon’s research addresses a critical challenge in robotics: how to train agents efficiently and safely in real-world settings where obstacles are not static but can be manipulated. By structuring the learning process as a curriculum, his work accelerates training convergence and improves performance across diverse scenarios. This approach has significant implications for autonomous vehicles, service robots, and warehouse automation. Jeon’s contributions are notable for bridging the gap between theoretical reinforcement learning and practical, deployable robotic systems, making him a rising voice in the quest for more adaptive and resilient autonomous navigation.
Research Focus
Key Achievements
Top Papers
- 1