Papers
2
Total Citations
12
H-Index
2
About
Tengyun Li is a leading researcher in mobile robotics, specializing in autonomous navigation, path planning, and long-term localization in dynamic environments. Their work addresses critical challenges in enabling robots to operate safely and efficiently in real-world settings. Li’s most influential contribution is the development of the MSIAR-GWO algorithm for mobile robot path planning, which enhances the traditional gray wolf optimizer to improve route efficiency and safety—a paper that has already garnered 7 citations since its 2025 publication. Equally impactful is their 2024 study on real-time submap trimming for map updating, which solves the problem of redundant information accumulation during long-term robot localization in changing environments, earning 5 citations. This work is pivotal for maintaining accurate navigation without overwhelming computational resources. Li’s research bridges theoretical optimization and practical deployment, offering scalable solutions for autonomous systems. Their achievements highlight a commitment to advancing robot autonomy, making them a notable figure in the field. For students and researchers, Li’s work exemplifies how algorithmic innovation can directly enhance real-world robotic performance.
Research Focus
Key Achievements
Top Papers
- 1Research on Mobile Robot Path Planning Based on MSIAR-GWO Algorithm7 citations · 2025
- 2