Xiangyi Ren
Papers
2
Total Citations
5
H-Index
2
About
Xiangyi Ren is a robotics researcher whose work focuses on the control and motion planning of complex robotic systems, particularly wheeled mobile robots (WMRs) and redundant manipulators. Ren’s major contributions include developing novel inverse kinematics solutions for seven-degree-of-freedom robotic arms using neural networks, combining the Minimum Velocity Norm scheme with damped least-squares methods to enable stable, singularity-avoiding motion. More recently, Ren has advanced trajectory tracking control for WMRs operating on uneven terrain, introducing a fixed-time generalized variable gain extended state observer (VGESO) to improve robustness and accuracy under challenging road conditions. This work, published in 2025, establishes a mapping between velocity and position for uneven surfaces and integrates an adaptive kinematic controller to enhance performance. While still early in their career, with papers accumulating citations in the single digits, Ren’s research demonstrates a strong foundation in applied control theory and nonlinear dynamics. Their work is particularly relevant for autonomous navigation in unstructured environments, with potential applications in field robotics and industrial automation.
Research Focus
Key Achievements
Top Papers
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