Xiaoyang Cao

Papers

Total Citations

117

H-Index

About

Xiaoyang Cao is a leading researcher at the intersection of robotics, sustainable design, and digital twin technology. His work focuses on developing intelligent detection robotics and low-carbon product optimization, where he has made significant contributions to integrating data fusion with sustainable manufacturing. Cao’s most influential paper, “Data fusion-based sustainable digital twin system of intelligent detection robotics” (2020), has garnered 70 citations, establishing a framework for real-time environmental monitoring and carbon footprint reduction in robotic systems. He further advanced the field with his studies on underactuated robotics kinematics for product carbon footprint (26 citations) and skeleton model-based low carbon design optimization (21 citations), both published in 2020. These works demonstrate his ability to bridge theoretical kinematics with practical sustainability challenges. Cao’s research is notable for its interdisciplinary approach, combining robotics, lifecycle assessment, and digital twin modeling to create actionable solutions for green manufacturing. His achievements highlight a commitment to reducing industrial environmental impact through intelligent automation, making him a key figure in sustainable robotics and design optimization.