Qinhui Liu
Papers
1
Total Citations
18
H-Index
1
About
Qinhui Liu is a leading researcher in mobile robotics and autonomous navigation, with a primary focus on real-time dynamic path planning for complex environments. Their most cited work, a 2021 study combining the artificial potential field method with a biased target Rapidly-exploring Random Tree (RRT) algorithm, has garnered 18 citations and addresses a critical challenge: enabling robots to efficiently and safely navigate unpredictable, dynamic settings. By integrating the local reactivity of potential fields with the global exploration capabilities of RRT, Liu’s algorithm significantly improves path smoothness and computational speed, offering a practical solution for applications from warehouse logistics to autonomous driving. This contribution stands out for its balance of theoretical rigor and real-world applicability, providing a foundation for subsequent advances in obstacle avoidance and real-time decision-making. Liu’s research continues to influence the development of more intelligent, adaptive robotic systems, making their work essential reading for students and engineers seeking to push the boundaries of autonomous navigation.
Research Focus
Key Achievements
Top Papers
- 1