Yang Tang
Papers
10
Total Citations
143
H-Index
7
About
Yang Tang is a specialized robotics researcher whose work sits at the intersection of automation, trajectory optimization, and surface modeling, with a particular focus on spray painting robots. Over the course of a prolific research career spanning more than a decade, Tang has made significant contributions to solving one of industrial robotics' most persistent challenges: achieving uniform, high-quality paint coverage across complex three-dimensional surfaces. Tang's most influential contributions include developing novel paint deposition rate models — most notably for electrostatic rotating bell systems — and pioneering the application of Bézier curves and exponential mean Bézier methods to trajectory planning, earning 27 and 20 citations respectively for these foundational works. His research systematically addresses both path geometry and end-effector velocity optimization, ensuring computational efficiency alongside coating uniformity. His 2019 work on 3D entity spraying introduced a finite range model and surface patching methodology that extended these techniques beyond curved surfaces to complex volumetric objects. Collectively accumulating over 140 citations, Tang's body of work has become an important reference point for researchers and engineers advancing automated painting systems in manufacturing. His experimental validation approaches, combining mathematical modeling with real-world spraying trials, lend particular credibility and practical applicability to his findings.
Research Focus
Key Achievements
Top Papers
- 1
- 2Optimized Combination of Spray Painting Trajectory on 3D Entities22 citations · 2019
- 3
- 4Automatic Spray Trajectory Optimization on Bézier Surface19 citations · 2019
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- 7
- 8Tool trajectory planning of painting robot and its experimental5 citations · 2014
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- 10