Shaosheng Xu
Papers
2
Total Citations
3
H-Index
1
About
Shaosheng Xu is a researcher focused on advancing robotic perception and multi-agent coordination, with particular expertise in sensor fusion, localization, and error compensation for robotic systems. His work addresses critical challenges in industrial automation, specifically improving the accuracy and robustness of multi-robot arm systems through innovative sensor integration. His most cited paper, "Control principle and error estimation for inverse trajectory method under locating error with optimization" (2021), established foundational methods for trajectory optimization under positioning uncertainties. His notable 2024 contribution, "Position Correction and Coordinate System Fusion for Multi-Robot Arm Systems Using Multiple LiDAR Sensors," introduces an enhanced adaptive Extended Kalman Filter (A-EKF) that dynamically adjusts process and measurement noise covariance, significantly improving coordinate system fusion accuracy in multi-robot environments. While his citation counts are currently modest (2 and 1 citations respectively), his work represents emerging contributions to the practical deployment of collaborative robotic systems. Xu’s research bridges theoretical control principles with real-world sensor fusion challenges, offering valuable solutions for industries requiring precise multi-robot coordination, such as automated manufacturing and logistics.
Research Focus
Key Achievements
Top Papers
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- 2