Yunzhi Huang
Papers
6
Total Citations
65
H-Index
4
About
Yunzhi Huang is a rising researcher in robotics, specializing in motion planning, human–robot interaction, and control for complex robotic systems. Their work addresses critical challenges in enabling safe, intuitive, and efficient robot operation in constrained and dynamic environments. Huang’s most impactful contribution is a novel path planning algorithm for narrow passages using an improved Probabilistic Roadmap Method (PRM), which has garnered 24 citations since 2024. They have also pioneered variable admittance control strategies for physical human–robot interaction, achieving 15 citations for a 2023 paper that deduces intuitive human intention to enhance safety and mitigate force impact. Further notable contributions include dynamic obstacle avoidance for mobile robots using an adaptive velocity obstacle method (11 citations) and shape-controllable inverse kinematics for hyper-redundant robots based on an improved FABRIK method (10 citations). Huang’s work on adaptive and iterative learning control for simultaneous force and direction control in grinding tasks, as well as energy-based admittance control for human–robot–environment interaction, demonstrates a sustained focus on practical, real-world applications. With a growing citation record and a clear trajectory toward advancing robot autonomy and safety, Huang is establishing themselves as a key contributor to modern robotics.
Research Focus
Key Achievements
Top Papers
- 1Robot path planning in narrow passages based on improved PRM method24 citations · 2024
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