Chenjin Zhang

Papers

Total Citations

H-Index

About

Chenjin Zhang is a researcher in robotics and computer vision, with a primary focus on enhancing the perceptive capabilities of humanoid service robots. Their most cited work, "Real-Time Object Recognition Based on NAO Humanoid Robot" (2018), addresses a critical challenge in service robotics: enabling robots to accurately and swiftly recognize objects in indoor environments. By leveraging advances in computer vision, Zhang’s research bridges the gap between theoretical object recognition techniques and practical, real-time deployment on platforms like the NAO robot. This work contributes to the broader goal of making service robots more autonomous and responsive in human-centric spaces, such as homes and offices. While the paper has garnered 3 citations, its significance lies in its foundational approach to integrating deep learning with resource-constrained robotic systems. Zhang’s contributions are particularly relevant for students and researchers exploring the intersection of robotics, embedded systems, and real-time vision, offering a practical framework for improving human-robot interaction through enhanced perceptual intelligence.