Papers

2

Total Citations

15

H-Index

2

About

Yilin Lang is a researcher at the forefront of bio-inspired robotics and human–robot collaboration, with a focus on developing safer, more intuitive interaction systems. Their key research areas include soft robotic actuation, particularly through antagonistic McKibben muscles, and motion control for physical human–robot-environment interaction. Lang’s most cited work, “Control of Antagonistic McKibben Muscles via a Bio-inspired Approach” (2022, 11 citations), introduces a novel method for mimicking biological muscle coordination to achieve compliant, efficient robotic movement. Building on this, their 2024 paper, “A Motion Control Approach for Physical Human–Robot-Environment Interaction via Operational Behaviors Inference” (4 citations), addresses a critical challenge in collaborative robotics: reducing human–robot conflicts by inferring human intentions and optimizing motion planning accordingly. This work has significant implications for industrial and assistive robotics, where seamless cooperation is essential. Lang’s research not only advances theoretical frameworks but also offers practical solutions for real-world applications, making their contributions highly relevant for students and researchers exploring the intersection of bio-inspired design and intelligent control systems.

Research Focus

Key Achievements

2
H-Index
2
Papers
15
Total Citations
8
Avg Citations/Paper
🏆 Most Cited Paper
Control of Antagonistic McKibben Muscles via a Bio-inspired Approach
11 citations · 2022
📈 Most Prolific Year: 2022 (1 Papers)
🤝 Key Collaborators: 6
🏛 Institutions: Zhejiang University of Technology, Zhejiang University

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago