Chia-Lien Li

Papers

Total Citations

H-Index

About

Chia-Lien Li is a researcher in robotics and computer vision, with a focus on enabling robots to operate effectively in complex, unstructured environments. Her most-cited work, "Robot grasping in dense clutter via view-based experience transfer" (2021), introduces a novel approach that allows robotic systems to learn and transfer grasping strategies from limited visual experiences, significantly improving performance in cluttered settings. This contribution addresses a critical challenge in autonomous manipulation, where traditional methods often fail due to occlusion and variability. With 4 citations, this paper has already garnered attention for its practical implications in warehouse automation and assistive robotics. Li’s research bridges perception and action, leveraging view-based learning to reduce the need for extensive training data. Her work is notable for its emphasis on transferability and efficiency, making it a valuable resource for students and researchers exploring robotic grasping, reinforcement learning, or scene understanding. By tackling real-world constraints like dense clutter, Li is helping to advance the frontier of dexterous robot interaction.