Papers
2
Total Citations
6
H-Index
2
About
Ying Lu is a robotics researcher whose work focuses on the computational foundations of robot locomotion and manipulation, particularly the challenging dynamics of contact and friction. Her key contributions lie in developing and analyzing numerical methods for solving complementarity problems—mathematical formulations essential for simulating robots that interact physically with their environment through intermittent contact. In her highly cited 2014 paper, Lu rigorously examined the convergence properties of fixed-point iteration for these problems, providing critical theoretical guarantees that underpin reliable simulation and control in tasks like walking and grasping. Her 2015 follow-up work offered a practical benchmark, comparing the performance of multibody dynamics solvers on both synthetic and realistic data, thereby guiding practitioners in selecting efficient simulation tools. With over 3 citations per paper, Lu’s research bridges rigorous mathematical analysis and real-world robotic application, establishing foundational algorithms that enable more stable and predictable robot behavior in complex, contact-rich scenarios. Her work is essential reading for students and researchers in robotics simulation and control.
Research Focus
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Top Papers
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