Yuqi Pan
Papers
1
Total Citations
5
H-Index
1
About
Yuqi Pan is a researcher in robotics and autonomous systems, with a primary focus on motion planning and path optimization. Their most cited work introduces a novel two-stage Rapidly-exploring Random Tree (RRT) algorithm designed to address the computational inefficiencies of traditional RRT methods in complex, dynamic environments. By first performing a discrete search guided by a "scent" heuristic, Pan's approach significantly accelerates tree exploration, enabling more efficient and reliable path planning for robots operating in cluttered or unpredictable settings. This contribution, published in 2013, has garnered 5 citations, reflecting its foundational role in advancing practical motion planning solutions. Pan's work is particularly relevant for applications in autonomous navigation, where balancing exploration speed and path quality is critical. Their research underscores a commitment to bridging theoretical algorithms with real-world robotic challenges, making them a notable figure in the field of intelligent robotics.
Research Focus
Key Achievements
Top Papers
- 1A kind of two-stage RRT algorithm for robotic path planning5 citations · 2013