Linzhao Hao

Papers

Total Citations

H-Index

About

Linzhao Hao is a researcher focused on intelligent robotics, automation, and computer vision, with a particular emphasis on integrating advanced sensing and control systems for practical applications. His work spans mobile robotics, manipulator control, and industrial automation, where he leverages deep learning and neural networks to enhance machine perception and decision-making. Hao’s most cited paper, “Design of mobile garbage collection robot based on visual recognition” (2020, 17 citations), introduces a novel system that combines path planning, visual scanning, and object identification for autonomous waste collection, addressing real-world environmental challenges. In “Research on Manipulator Tracking Control Algorithm Based on RBF Neural Network” (2021, 14 citations), he tackles the complexities of nonlinear manipulator dynamics by proposing a trajectory tracking method that exploits neural networks’ self-learning and parallel processing capabilities. His work on “Design of workpiece recognition and sorting system based on deep learning” (2021, 3 citations) further demonstrates his commitment to industrial efficiency, using deep learning models to enable robots to sort and pick objects based on visual input. Hao’s contributions are notable for their direct applicability to smart manufacturing and sustainable robotics, making him a promising voice in the field of autonomous systems.