About

Dengpeng Xing is a robotics researcher whose work spans humanoid robot control, precision assembly automation, and learning-based robotic manipulation. His research has made significant contributions across two complementary frontiers: the mechanics of multi-robot coordination and the intelligent control of human-like robotic systems. Xing's early work established him as an authority in humanoid locomotion and balance, with notable papers on disturbance observer-based joint control (25 citations), arm and trunk motion generation (25 citations), and gain-scheduled standing balance strategies — collectively advancing the robustness of bipedal robots under real-world perturbations. In parallel, his precision assembly research tackled the formidable challenge of coordinating multiple robot arms to manipulate irregular objects with interference and clearance fits, earning broad recognition with 28–31 citations per study. More recently, Xing has embraced deep learning and reinforcement learning paradigms, developing spatiotemporal transformer architectures for robotic reinforcement learning and diffusion policy methods for anthropomorphic hand piano playing — reflecting a forward-looking pivot toward embodied intelligence. His work on learning kinematics across heterogeneous serial robots further signals ambitions to generalize robotic intelligence at scale. Across a career spanning over a decade, Xing's research consistently bridges mechanical precision with intelligent autonomy.

Research Focus

Key Achievements

8
H-Index
17
Papers
177
Total Citations
10
Avg Citations/Paper
🏆 Most Cited Paper
Sensing and Control for Simultaneous Precision Peg-in-Hole Assembly of Multiple Objects
31 citations · 2019
📈 Most Prolific Year: 2010 (3 Papers)
🤝 Key Collaborators: 24
🏛 Institutions: Chinese Academy of Sciences, Shandong Institute of Automation, Shanghai Jiao Tong University, Institute of Automation, Beijing Academy of Artificial Intelligence, University of Chinese Academy of Sciences

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago