Yinkang He
Papers
1
Total Citations
2
H-Index
1
About
Yinkang He’s research centers on intelligent robotics and industrial automation, with a particular focus on motion planning and control optimization for underactuated systems. His most-cited work, “Intelligent route planning model of industrial robot based on inertia moment parameter optimization” (2021), introduces a novel method that leverages inertia moment parameter optimization to enhance the intelligent trajectory planning of monocular vision dynamic underactuated industrial robots. This contribution addresses critical challenges in real-time path generation and stability for robots operating in constrained environments, improving their adaptability and precision. While his citation count is modest, his work represents a foundational step in integrating dynamic parameter optimization with vision-based robotic control—a niche yet growing area in industrial robotics. He’s research is particularly valuable for advancing the autonomy of robots in manufacturing and logistics, where efficient route planning under dynamic conditions is essential. His approach offers a practical framework for future developments in intelligent robotic systems, making his contributions noteworthy for researchers exploring the intersection of computer vision, dynamics, and optimization in automation.
Research Focus
Key Achievements
Top Papers
- 1