Meini Wang
Papers
1
Total Citations
7
H-Index
1
About
Meini Wang is a researcher in robotics and motion planning, with a focus on developing efficient algorithms for high-dimensional systems operating in complex environments. Her most cited work introduces an improved Rapidly-exploring Random Tree (RRT) algorithm for collision-free motion planning, addressing critical challenges in robotic navigation. By integrating an Oriented Bounding Box (OBB)-based collision detection method using the Separating Axis Theorem, Wang’s approach enhances both the speed and reliability of pathfinding in cluttered settings. This work, published in 2012, has garnered 7 citations, reflecting its foundational role in advancing practical motion planning solutions. Wang’s contributions are particularly relevant to autonomous systems, where real-time obstacle avoidance and computational efficiency are paramount. Her research bridges theoretical algorithm design and real-world robotic applications, offering a robust framework for high-dimensional robot control. Through her innovative refinements to the RRT algorithm, Wang has helped pave the way for more adaptive and collision-aware robotic systems, making her work a valuable reference for students and researchers in robotics, artificial intelligence, and automation.
Research Focus
Key Achievements
Top Papers
- 1