Chaneun Park
Papers
3
Total Citations
16
H-Index
3
About
Chaneun Park is a robotics researcher whose work sits at the intersection of intelligent control, human-machine interaction, and assistive technology. Park’s primary research areas include reinforcement learning for robotic manipulation and autonomous navigation, as well as functional electrical stimulation (FES) for mobility assistance. In their highly cited 2023 paper, Park introduced a task decomposition and dedicated reward-system-based reinforcement learning algorithm for pick-and-place operations, breaking complex manipulation into subtasks to improve learning efficiency. Their 2024 work advanced autonomous mobile robot navigation in dynamic environments by combining deep deterministic policy gradient with reward shaping and hindsight experience replay, enabling robots to find optimal policies amid obstacles—a contribution with over six citations. Park also made a notable impact in assistive technology through their work on an FES-based robotic bike for the Cybathlon 2020 competition. This project integrated a fatigue-compensation algorithm and mechanism to help pilots with spinal cord injuries drive a bike using their paralyzed muscles, demonstrating a commitment to sustainable and accessible mobility. With each publication garnering early citations, Park is establishing a reputation for bridging theoretical reinforcement learning advances with real-world robotic and assistive applications.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3