Amy J. Wagoner Johnson
Papers
9
Total Citations
289
H-Index
7
About
Amy J. Wagoner Johnson is a pioneering researcher whose work bridges advanced control theory and biomedical engineering, with particular expertise in iterative learning control (ILC) and bone scaffold fabrication. Her most influential contribution — the Basis Task Approach to ILC, cited over 110 times — fundamentally expanded the flexibility of learning control systems by enabling trajectory and dynamics variation across trials, a longstanding limitation in the field. This framework, further refined through her work on bumpless transfer methods and basis signal libraries, has broad implications for precision manufacturing and robotic systems. Wagoner Johnson's research is distinctive in its translational reach: she applied sophisticated control algorithms directly to micro-robotic deposition (μRD), a fabrication technique for producing hydroxyapatite bone scaffolds. By integrating machine vision feedback into ILC and developing design-of-experiments guidelines for scaffold fabrication, she significantly advanced the reliability and quality of engineered bone substitutes. Her computational cellular solids approach to scaffold stiffness design further demonstrates her ability to connect materials science with clinical engineering needs. With nearly 290 citations across her most recognized works, Wagoner Johnson's contributions have meaningfully shaped both control systems research and tissue engineering scaffold design.
Research Focus
Key Achievements
Top Papers
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- 4Iterative Learning Control for robotic deposition using machine vision29 citations · 2008
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- 6Bumpless Transfer Filter for Exogenous Feedforward Signals23 citations · 2013
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- 8Iterative Learning Control using a basis signal library6 citations · 2009
- 9Cross Coupled Iterative Learning Control of Dissimilar Dynamical Systems3 citations · 2009