About

Weiwei Huang is a leading researcher in bipedal locomotion and humanoid robotics, with a focus on enabling stable, adaptive walking in complex environments. Their major contributions include developing real-time optimization-based walking controllers for full-size humanoids, as demonstrated in their highly cited 2013 work (83 citations), which uses a two-level optimization framework for center of mass and swing foot trajectory planning. Huang also pioneered pattern generation for walking on slopes and stairs using preview control of the zero moment point (50 citations), and advanced push recovery through walking phase modification (11 citations). Their research extends to cognitive robotics, with work on brain-like memory systems for robotic navigation (37 citations) and bio-inspired locomotion control using neural oscillators (10 citations). More recently, Huang has explored precision motion systems, including periodic-disturbance observers for atomic force microscopy (23 citations) and stiffness-tunable nanopositioners (20 citations). With over 250 total citations across their top papers, Huang’s work bridges theoretical optimization, biomechanics, and practical control, making significant impacts on humanoid robot stability and adaptability in real-world settings.

Research Focus

Key Achievements

9
H-Index
14
Papers
291
Total Citations
21
Avg Citations/Paper
🏆 Most Cited Paper
3D walking based on online optimization
83 citations · 2013
📈 Most Prolific Year: 2013 (4 Papers)
🤝 Key Collaborators: 24
🏛 Institutions: Carnegie Mellon University, National University of Singapore, Agency for Science, Technology and Research, Shanghai Jiao Tong University

Top Papers

  1. 1
  2. 2
  3. 3
  4. 4
  5. 5
  6. 6
  7. 7
  8. 8
  9. 9
  10. 10

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago