Papers
2
Total Citations
88
H-Index
2
About
Xuyan Qi is a leading researcher in mobile robot navigation and intelligent path planning, with a focus on developing robust, efficient algorithms for autonomous systems. Qi's major contributions center on advancing classical search and reinforcement learning methods for real-world robotic applications. Their most cited work, "An Efficient and Robust Improved A* Algorithm for Path Planning" (2021, 74 citations), addresses critical limitations in the conventional A* algorithm by enhancing both computational efficiency and path robustness, offering a practical solution for dynamic environments. Building on this, Qi introduced "ETQ-learning: an improved Q-learning algorithm for path planning" (2024, 14 citations), which refines reinforcement learning techniques to achieve faster convergence and more reliable navigation. These contributions have significantly impacted the field, providing foundational improvements that enable safer, more adaptive robot movement. Qi's work is widely recognized for bridging theoretical algorithm design with deployable robotic systems, making them a key figure in autonomous navigation research. Their ongoing efforts continue to shape the next generation of intelligent path planning methodologies.
Research Focus
Key Achievements
Top Papers
- 1An Efficient and Robust Improved A* Algorithm for Path Planning74 citations · 2021
- 2ETQ-learning: an improved Q-learning algorithm for path planning14 citations · 2024