Yipeng Tang
Papers
2
Total Citations
41
H-Index
2
About
Yipeng Tang is a robotics researcher whose work bridges autonomous navigation and precision manufacturing. His key research areas include path planning for mobile robots, hand-eye calibration for industrial automation, and machine learning applications in robotics. Tang’s most influential contribution is an enhanced dynamic Delaunay triangulation-based path planning algorithm for autonomous mobile robot navigation, published in 2009 with 25 citations. This work, developed in the context of the Intelligent Ground Vehicle Competition, provided a robust solution for real-time path planning in dynamic environments, enabling robots to navigate complex courses successfully. More recently, Tang has advanced industrial robotics with a novel semi-automatic hand-eye calibration process for laser profilometers, published in 2023 and already garnering 16 citations. This work integrates machine learning to automatically generate optimal calibration postures, significantly improving both efficiency and accuracy over traditional manual methods. Tang’s research demonstrates a consistent focus on practical, deployable solutions—from competition-grade autonomous navigation to high-precision manufacturing calibration—making his work valuable for both academic researchers and industry practitioners seeking to enhance robotic autonomy and precision.
Research Focus
Key Achievements
Top Papers
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- 2