Yongxu Chen
Papers
1
Total Citations
2
H-Index
1
About
Yongxu Chen is a robotics researcher whose work centers on intelligent automation, robotic manipulation, and vision-guided control systems for industrial and warehouse applications. His most notable contribution is the optimized design and deep vision-based operation control of a multi-functional robotic gripper for automatic loading systems, a study that has already garnered early attention with 2 citations since its 2025 publication. This work introduces a modular architecture integrating standardized platforms, transport containers, and multiple collaborative robotic arms, demonstrating how computer vision and deep learning can enhance real-time grasping and loading precision. Chen’s research addresses critical challenges in logistics automation, aiming to improve efficiency, adaptability, and safety in dynamic warehouse environments. His achievements reflect a strong commitment to bridging theoretical robotics with practical deployment, offering scalable solutions for modern supply chains. As an emerging voice in the field, Chen’s work is poised to influence future developments in autonomous material handling and human-robot collaboration.
Research Focus
Key Achievements
Top Papers
- 1