Weishi Hu

Huaqiao University

Papers

2

Total Citations

9

H-Index

2

About

Weishi Hu is a rising researcher in the field of robotic manipulation and intelligent control, with a focus on enabling robots to interact safely and precisely with unknown environments. His work addresses a critical challenge in modern robotics: achieving stable, accurate force tracking during physical contact, even when environmental dynamics are uncertain or time-varying. Hu’s major contributions include the development of an **Intelligent Impedance Control (IIC) strategy** that integrates model-based insights with expert-guided deep reinforcement learning, allowing robotic manipulators to adapt their force–motion behavior in real time. This work, published in 2025, has already garnered 6 citations, signaling its immediate impact. Earlier, he explored **Active Disturbance Rejection Control (ADRC)** for contact force tracking, tackling issues like transient overshoot and steady-state error that plague traditional impedance controllers. By combining theoretical rigor with practical simulation and experimental validation, Hu is pushing the boundaries of adaptive, learning-based control—a vital step toward robots that can work alongside humans in unstructured settings. His research is particularly relevant for students and engineers interested in the intersection of control theory, reinforcement learning, and physical human-robot interaction.

Research Focus

Key Achievements

2
H-Index
2
Papers
9
Total Citations
5
Avg Citations/Paper
🏆 Most Cited Paper
Intelligent Impedance Strategy for Force–Motion Control of Robotic Manipulators in Unknown Environments via Expert-Guided Deep Reinforcement Learning
6 citations · 2025
📈 Most Prolific Year: 2025 (1 Papers)
🤝 Key Collaborators: 7
🏛 Institutions: Huaqiao University

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago