Zhipeng Dong
Papers
9
Total Citations
153
H-Index
5
About
Zhipeng Dong is a robotics researcher whose work bridges the gap between complex human manipulation and autonomous robotic systems. His primary research areas include bimanual non-prehensile manipulation, dexterous functional grasping, and learning from demonstration for humanoid robots. Dong’s most notable contribution is his pioneering work on robot cooking, where he developed a bimanual system capable of performing the highly dynamic Chinese stir-fry technique—a task requiring coordinated, rhythmic movements that challenge even human chefs. This work, published in 2022, has garnered 78 citations and stands as his most influential paper. He has also made significant strides in industrial automation, developing the Vector Detection Network for autonomous reading of analog meters in the wild (20 citations), and in humanoid dexterity with a language-guided framework for functional grasping (16 citations). His 2025 work on cross-embodiment skill transfer between humans and humanoids, HOTU, represents a leap forward in enabling humanoid robots to learn complex loco-manipulation tasks. Dong’s research consistently targets real-world, high-impact applications, from household robotics to waste sorting and even piano playing, demonstrating a rare blend of theoretical depth and practical ingenuity.
Research Focus
Key Achievements
Top Papers
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- 7Regrasping on Printed Circuit Boards with the Smart Suction Cup2 citations · 2024
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- 9HoPE: Horizontal Plane Extractor for Cluttered 3D Scenes2 citations · 2018