Sarah S. Lam
Papers
2
Total Citations
216
H-Index
2
About
Sarah S. Lam is a distinguished researcher specializing in robotics kinematics and computational intelligence, with a particular focus on parallel manipulator systems. Her work addresses one of the most challenging problems in robotics engineering: solving the forward kinematics problem in parallel manipulators — closed kinematic structures prized for their exceptional rigidity, high payload-to-weight ratios, and broad applicability across manufacturing, flight simulation, and medical robotics. Lam's most influential contribution, her 2005 paper introducing a hybrid strategy to solve the forward kinematics problem in parallel manipulators, has garnered 130 citations, establishing her as a leading voice in kinematic control methodology. Recognizing the computational complexity inherent in closed-loop structures, she pioneered the integration of artificial neural networks into iterative kinematic solving strategies, as demonstrated in her 2008 follow-up work, which has accumulated 86 citations. Together, these publications reflect a coherent and progressive research vision that bridges classical mechanical engineering with modern machine learning techniques. Her contributions have proven invaluable to engineers and researchers designing next-generation robotic systems, offering robust, computationally efficient alternatives to traditional analytical methods that often struggle with the nonlinear complexity of parallel mechanisms.
Research Focus
Key Achievements
Top Papers
- 1
- 2