Yi-Lin Wei

Ministry of Education of the People's Republic of China

Papers

Total Citations

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About

Yi-Lin Wei is a rising researcher in robotic manipulation and embodied AI, whose work centers on bridging language and physical action for dexterous grasping. His key contributions lie in developing frameworks that enable robots to understand and execute complex grasp tasks guided by human commands. In his highly cited 2024 paper, "An Economic Framework for 6-DoF Grasp Detection" (14 citations), Wei introduced a cost-efficient approach to detect optimal grasp poses, significantly reducing computational overhead while maintaining accuracy. His most innovative work, "Grasp as You Say: Language-guided Dexterous Grasp Generation" (4 citations), pioneers the novel task "Dexterous Grasp as You Say" (DexGYS). This research tackles a critical gap by enabling robots to perform dexterous grasping based on natural language instructions, moving beyond simple object recognition to understand human intent. Wei identified that progress in this field is hindered by the lack of datasets with natural human guidance, and his work proposes solutions to generate such data. His research has immediate implications for assistive robotics and human-robot collaboration, where intuitive communication is essential. With a focus on making robotic grasping more accessible and responsive, Yi-Lin Wei is shaping the future of language-guided physical interaction.