Papers

5

Total Citations

51

H-Index

3

About

Yuanchen Ju is an emerging researcher at the forefront of robot manipulation and embodied intelligence, with work spanning affordance generalization, distributed manipulation, and robot-assisted caregiving. His most recognized contribution, "Robo-ABC" (32 citations), tackles one of robotics' most persistent challenges: enabling robots to generalize manipulation skills to unfamiliar objects by leveraging semantic correspondence — mirroring how humans intuitively transfer interaction experience across object categories. This work represents a meaningful step toward open-world robotic intelligence. In "ArrayBot" (12 citations), Ju explores a novel distributed manipulation platform using a 16×16 array of tactile-integrated sliding pillars, combining perception and manipulation in a unified hardware-software framework governed by reinforcement learning. His work on "GRACE" extends his research into socially consequential domains, developing personalized robot caregiving systems that respect user agency and functional diversity. Further contributions on pairwise object assembly demonstrate a consistent commitment to generalizable, real-world robot capabilities. Collectively accumulating nearly 50 citations across recent publications, Ju's research charts an ambitious trajectory toward robots that perceive, adapt, and assist across the full complexity of human environments.

Research Focus

Key Achievements

3
H-Index
5
Papers
51
Total Citations
10
Avg Citations/Paper
🏆 Most Cited Paper
Robo-ABC: Affordance Generalization Beyond Categories via Semantic Correspondence for Robot Manipulation
32 citations · 2024
📈 Most Prolific Year: 2024 (3 Papers)
🤝 Key Collaborators: 22
🏛 Institutions: ShangHai JiAi Genetics & IVF Institute, Cornell University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago