Papers
2
Total Citations
90
H-Index
2
About
Zhengli Xiao is a leading researcher in nonlinear control theory and robotic motion planning, with a focus on overcoming fundamental computational and control challenges. Their most influential work addresses the long-standing division-by-zero (DBO) problem—traditionally known as control singularity—in nonlinear systems. In a highly cited 2016 paper (79 citations), Xiao introduced the Zhang dynamics (ZD) and Zhang-gradient (ZG) methods, providing a rigorous framework for conquering singularities that previously destabilized controllers. This contribution has been pivotal for advancing robust control in complex autonomous systems. Xiao also made significant strides in redundant robot manipulator motion planning, proposing an acceleration-level minimum kinetic energy (MKE) scheme (2014, 11 citations) that leverages the Ma equivalence to achieve energy-efficient, pseudo-inverse-based trajectory generation. This work directly improves the performance and safety of industrial and service robots. With a career dedicated to bridging theoretical mathematics and practical robotics, Xiao’s research continues to inspire new approaches to singularity avoidance and optimal motion control, earning recognition for its clarity, originality, and real-world applicability.
Research Focus
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Top Papers
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