Jianyu Tang
Papers
2
Total Citations
60
H-Index
2
About
Jianyu Tang is a robotics researcher whose work focuses on advancing the autonomy and precision of industrial robot manipulators. His key research areas include path planning, adaptive control, and sensor-based tracking for manufacturing automation. Tang’s most notable contribution is his novel manipulability-based path planning strategy, which integrates manipulability measures into the RRT* algorithm to simultaneously optimize path length and robot dexterity—a paper that has garnered 57 citations since 2023. He has also developed a photogrammetry-based dynamic path tracking method that combines adaptive neuro-PID control with a robust Kalman filter, enabling real-time pose correction using stereo camera feedback. This work addresses critical challenges in high-precision industrial tasks. While still early in his career, Tang’s integration of manipulability constraints into sampling-based planners represents a significant step toward more capable and efficient robotic systems. His research is particularly relevant for applications in automated manufacturing, where both path efficiency and task feasibility are paramount.
Research Focus
Key Achievements
Top Papers
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