Papers

2

Total Citations

8

H-Index

1

About

Yanhui Lai is a researcher specializing in intelligent optimization algorithms, neural networks, and robotic control systems. Their most impactful work focuses on enhancing trajectory tracking for robotic arms through hybrid computational models. In their highly cited 2025 study, Lai introduced the Mapping Mountain Gazelle Optimizer (MMGO), a novel improvement upon the standard Mountain Gazelle Optimizer (MGO). This algorithm was integrated with neural networks to significantly improve the precision and efficiency of robotic arm trajectory tracking, a critical challenge in industrial automation and advanced manufacturing. The paper has already garnered 7 citations, indicating growing recognition in the field. Additionally, Lai contributed to practical manufacturing applications with their 2019 work on laser vision-based determination of initial welding points for multi-pass welding. This research demonstrates a keen ability to bridge theoretical algorithm development with real-world engineering solutions. Yanhui Lai’s work is particularly relevant for students and researchers interested in the intersection of bio-inspired optimization, deep learning, and robotics, offering innovative approaches to complex control problems.

Research Focus

Key Achievements

1
H-Index
2
Papers
8
Total Citations
4
Avg Citations/Paper
🏆 Most Cited Paper
Research on the application of a model combining improved optimization algorithms and neural networks in trajectory tracking of robotic arms
7 citations · 2025
📈 Most Prolific Year: 2025 (1 Papers)
🤝 Key Collaborators: 7
🏛 Institutions: Wuhan University of Technology, Shanghai Jiao Tong University

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago