Xinyang Guo

Kunming University of Science and Technology

Papers

1

Total Citations

8

H-Index

1

About

Xinyang Guo is a leading researcher in industrial robotics, specializing in kinematic calibration, parameter identification, and error compensation to enhance robotic precision. Their most-cited work introduces an innovative approach using an Unscented Kalman Filter with adaptive process noise covariance, addressing the limitations of traditional linearization-based methods. This contribution significantly improves absolute positioning accuracy in industrial robots, a critical factor for advanced manufacturing and automation. With 8 citations already, this 2024 paper underscores Guo’s impact in advancing robotic performance through robust, real-time error correction. Their research bridges theoretical modeling and practical application, offering scalable solutions for high-precision tasks. Guo’s work is pivotal for students and engineers seeking to understand and implement state-of-the-art kinematic calibration techniques, positioning them as a key figure in the evolution of intelligent robotic systems.

Research Focus

Key Achievements

1
H-Index
1
Papers
8
Total Citations
8
Avg Citations/Paper
🏆 Most Cited Paper
Kinematic Parameter Identification and Error Compensation of Industrial Robots Based on Unscented Kalman Filter with Adaptive Process Noise Covariance
8 citations · 2024
📈 Most Prolific Year: 2024 (1 Papers)
🤝 Key Collaborators: 4
🏛 Institutions: Kunming University of Science and Technology

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago