Papers
30
Total Citations
840
H-Index
15
About
Jixiang Yang is a prominent researcher specializing in robotic manufacturing, motion control, and intelligent automation, with particular expertise in robotic machining, stiffness modeling, and precision path planning. His work addresses fundamental challenges in deploying industrial robots for high-accuracy manufacturing tasks, areas where traditional automation struggles to meet stringent precision demands. Yang's most influential contributions center on improving the geometric and force-control accuracy of 6R serial robots. His development of C3-continuous corner smoothing algorithms for tool path planning has advanced robotic motion efficiency, while his pose-dependent stiffness modeling and compensation frameworks have significantly reduced contour errors in robotic milling and grinding operations — problems that have long limited robots from replacing rigid machine tools. His research on workpiece placement optimization and end-effector pose selection demonstrates a sophisticated systems-level approach to minimizing deformation-induced inaccuracies. More recently, Yang has extended his reach into agricultural intelligence, with a highly cited lightweight tomato ripeness detection algorithm demonstrating versatility across domains. With several papers surpassing 70 citations within just two to three years of publication, Yang's research has garnered considerable recognition from the robotics and manufacturing engineering communities, establishing him as an influential voice in precision robotic automation.
Research Focus
Key Achievements
Top Papers
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- 9Bagging for Gaussian mixture regression in robot learning from demonstration32 citations · 2020
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