Papers
3
Total Citations
18
H-Index
3
About
Lixin Wei is a pioneering researcher in robotics and intelligent control systems, with a career spanning two decades of advancing robot autonomy and precision manipulation. His work centers on three key areas: mobile robot navigation in unknown environments, friction compensation for precise robot control, and adaptive neural network-based position/force control. Wei's most impactful contribution is his 2024 paper on "Mobile robot path planning based on multi-experience pool deep deterministic policy gradient in unknown environment," which has already garnered 10 citations, demonstrating its immediate relevance to the field of reinforcement learning for autonomous navigation. His earlier foundational work in 2005 on observer-based friction compensation, with 5 citations, introduced a novel approach using the LuGre friction model to observe undetectable presliding displacement and low-speed dynamics, combined with adaptive parameter identification for PD+ feedforward robust control. In 2006, Wei advanced adaptive neural network position/force control for robot manipulators with model uncertainties, integrating neural network modeling with self-tuning fuzzy control to handle force-position relationships. His research bridges classical control theory with modern machine learning, offering practical solutions for robots operating in complex, uncertain environments.
Research Focus
Key Achievements
Top Papers
- 1
- 2Observer based friction compensation in robot control5 citations · 2005
- 3