Jieyang Peng
Papers
2
Total Citations
29
H-Index
2
About
Dr. Jieyang Peng is a leading researcher at the intersection of robotics, deep learning, and intelligent manufacturing. His work focuses on equipping robotic systems with advanced perception and adaptive control capabilities, particularly for smart factory and automated assembly environments. Dr. Peng’s most influential contribution is a deep-learning-based framework for object classification using tactile robot hands, which enables robots to identify and manipulate components through touch—a critical capability for flexible production lines. This work has garnered 18 citations and is foundational for integrating tactile sensing into Industry 4.0. More recently, he pioneered a meta-learning enhanced adaptive control strategy for automated PCB assembly, achieving 11 citations by enabling robots to rapidly adjust to new tasks with minimal data. This approach significantly reduces reprogramming time and boosts manufacturing efficiency. Dr. Peng’s research not only advances robotic dexterity but also bridges the gap between simulation and real-world deployment. His achievements are vital for students and engineers seeking to build more autonomous, resilient, and intelligent robotic systems for the factories of tomorrow.
Research Focus
Key Achievements
Top Papers
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