Weizhao Chen

South China University of Technology, Beijing Information Science & Technology University

Papers

Total Citations

H-Index

About

Weizhao Chen is a researcher focused on advancing robotics and autonomous systems, with key contributions in motion control and computer vision. His work addresses critical challenges in robot stability and object recognition under real-world constraints. His most cited paper, "AGV Motion Balance and Motion Regulation Under Complex Conditions" (2022), with 11 citations, proposes novel control strategies for automated guided vehicles navigating uneven or unpredictable environments, enhancing operational safety and efficiency. Additionally, his research "Research on Classification and Detection System of Common Household Tools for Home Service Robot" (2020) tackles the pressing issue of deploying deep learning vision algorithms on resource-limited robotic platforms. By addressing limited storage, long prediction times, and weak computational power, Chen’s work enables more practical and responsive home service robots. His contributions bridge the gap between theoretical deep network models and real-time, embedded robotic applications. With a growing citation impact, Chen is establishing himself as a thoughtful engineer-scientist, dedicated to making robots more adaptive, intelligent, and useful in daily life—paving the way for next-generation autonomous service systems.