About

Jijie Xu is a robotics researcher whose work spans dexterous robotic manipulation, multifingered hand systems, and assistive robotics technologies. Over the course of his career, Xu has made foundational contributions to the theoretical and computational understanding of how robotic hands perform complex, large-scale manipulation tasks — particularly through the study of finger gaits, the strategic repositioning of robotic fingers that enables manipulation beyond what simple rolling or sliding motions can achieve. Xu's most influential body of work develops kinematic and planning frameworks for multifingered robotic hands, including pioneering the use of hybrid automaton models to formally capture the discrete and continuous dynamics of finger gaiting. His sampling-based planning algorithms brought practical computational solutions to this challenging problem, collectively earning dozens of citations across the robotics community. His 2008 hybrid automaton model alone has garnered 23 citations, reflecting its lasting methodological impact. Beyond manipulation theory, Xu contributed to applied assistive robotics through his work on the Personal Mobility and Manipulation Appliance (PerMMA), a robotic system designed to restore functional independence for individuals with severe physical disabilities — his most-cited contribution with 26 citations. Together, his research bridges rigorous theoretical foundations with meaningful real-world human benefit.

Research Focus

Key Achievements

5
H-Index
8
Papers
109
Total Citations
14
Avg Citations/Paper
🏆 Most Cited Paper
Performance evaluation of The Personal Mobility and Manipulation Appliance (PerMMA)
26 citations · 2013
📈 Most Prolific Year: 2007 (2 Papers)
🤝 Key Collaborators: 15
🏛 Institutions: University of Pittsburgh, Hong Kong University of Science and Technology, Rochester Institute of Technology, University of Hong Kong

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago