Huipin Lin

Papers

Total Citations

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About

Huipin Lin is a researcher advancing intelligent robotic systems, with a focus on computer vision, nonlinear control, and autonomous manipulation. Their most cited work, "A Hybrid YOLOv4 and Particle Filter Based Robotic Arm Grabbing System in Nonlinear and Non-Gaussian Environment" (2021, 17 citations), introduces a novel approach to robotic arm grasping that integrates deep learning-based object detection with robust state estimation. By combining YOLOv4 for real-time visual recognition and a particle filter for tracking in challenging nonlinear and non-Gaussian conditions, Lin addresses a critical gap in robotic precision—enabling accurate grasping even when environmental noise and unpredictable motion disrupt conventional methods. This contribution is particularly significant for applications in manufacturing, logistics, and assistive robotics, where reliability under uncertainty is paramount. Lin’s work demonstrates a practical fusion of vision and tracking, offering a scalable solution for autonomous systems operating in complex, real-world settings. Their research continues to influence the development of more adaptive and resilient robotic arms, bridging the gap between theoretical control methods and deployable intelligent hardware.