Jen‐Hui Chuang
Papers
7
Total Citations
46
H-Index
4
About
Jen-Hui Chuang has made pioneering contributions to robotic path planning, particularly through potential-based algorithms for articulated manipulators. His core research focuses on developing collision-free motion strategies for high-degree-of-freedom (DOF) robots, including hyper-redundant systems and those with moving bases. Chuang’s major innovation lies in generalizing potential field models—inspired by electrostatic repulsion—to directly compute repulsive forces and torques in 3-D workspace, bypassing the expensive configuration-space preprocessing required by traditional methods. His most cited works, including “Potential-based path planning for robot manipulators” (2005, 12 citations) and “A novel potential-based path planning of 3-D articulated robots with moving bases” (2004, 12 citations), demonstrate the effectiveness of this approach for both 3-DOF and 2-DOF joints. More recently, Chuang has extended his expertise into real-time monocular depth estimation using lightweight neural networks (2021), bridging classical robotics with modern deep learning for autonomous driving and environment sensing. With over 40 cumulative citations across his key papers, Chuang’s work continues to influence efficient, practical motion planning in complex robotic systems.
Research Focus
Key Achievements
Top Papers
- 1Potential-based path planning for robot manipulators12 citations · 2005
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- 3Potential-based path planning for robot manipulators in 3-D workspace11 citations · 2004
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- 7A Potential-Based Path Planning of Articulated Robots with 2-DOF Joints2 citations · 2006