Zhongyi Huang

Papers

Total Citations

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About

Zhongyi Huang is a researcher whose work bridges advanced manufacturing and intelligent robotics, with a focus on robotic additive manufacturing and autonomous navigation. His most cited paper, "Optimization-based non-equidistant toolpath planning for robotic additive manufacturing with non-underfill orientation" (2023, 17 citations), introduces a novel approach to toolpath optimization that minimizes material underfill and enhances structural integrity in 3D printing processes—a critical contribution to the efficiency and quality of large-scale robotic fabrication. Earlier, Huang made significant strides in autonomous systems with his 2015 paper "A new method for obstacle detection based on Kinect depth image" (12 citations), which addresses a key challenge in intelligent transportation and robot navigation by leveraging depth-sensing technology to improve detection accuracy and reliability. This work has implications for safer, more responsive autonomous vehicles and mobile robots. With a combined citation impact of nearly 30 citations, Huang’s research demonstrates a clear trajectory from foundational sensing techniques to applied manufacturing optimization, marking him as a promising contributor to the fields of additive manufacturing and robotics.