Jeonghyeon Wang
Papers
3
Total Citations
17
H-Index
2
About
Jeonghyeon Wang is a robotics researcher specializing in motion and path planning for autonomous systems, with a focus on overcoming complex environmental and kinematic constraints. His work addresses critical challenges in both mobile robot navigation and manipulator control. Wang’s most influential contribution is the development of the Weighted Virtual Tangential Vector (WVTV) algorithm, which provides a real-time solution to the notorious “U-shaped enclosure” problem—a common failure mode for local path planners. This work, with 9 citations, demonstrates his ability to balance driving safety with goal achievement. He has also advanced sampling-based planning for high-degree-of-freedom systems, proposing a Rapidly-exploring Random Trees (RRT) method for a 7DOF manipulator that ensures both collision-free and occlusion-free paths (6 citations). Further extending his impact, Wang introduced a constrained motion planning algorithm that leverages local geometric information to efficiently navigate path constraints in manipulator joint spaces (2 citations). Through these contributions, Wang has provided practical, computationally efficient solutions that enhance the autonomy and reliability of robotic systems in cluttered and constrained environments.
Research Focus
Key Achievements
Top Papers
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