Shang Liu

Beihang University, Carnegie Mellon University

Papers

2

Total Citations

4

H-Index

2

About

Shang Liu is a researcher at the intersection of robotics, manipulation, and adaptive architectural systems. Her work focuses on enabling robots to interact with unstructured environments through robust perception and control. In her highly cited 2023 paper, she developed a novel method for grasp pose adaptation that fuses RGBD camera data with force/torque sensing, allowing robots to dynamically adjust their grip based on the object's center of mass—a critical advance for handling irregular or fragile items. This work has garnered 2 citations and demonstrates her strength in sensor integration. Earlier, in 2019, Liu explored the frontier of architectural robotics by designing an actuated, active transforming structure that responds to human presence via face detection. This project, also with 2 citations, showcases her ability to merge mechanical design with real-time sensing, envisioning buildings that can physically reconfigure themselves. Through these contributions, Shang Liu is shaping a future where robots and built environments are more responsive, safe, and intelligent.

Research Focus

Key Achievements

2
H-Index
2
Papers
4
Total Citations
2
Avg Citations/Paper
🏆 Most Cited Paper
Center-of-Mass-Based Robust Grasp Pose Adaptation Using RGBD Camera and Force/Torque Sensing
2 citations · 2023
📈 Most Prolific Year: 2023 (1 Papers)
🤝 Key Collaborators: 7
🏛 Institutions: Beihang University, Carnegie Mellon University

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago