K. Dupree
Papers
9
Total Citations
153
H-Index
7
About
K. Dupree is a robotics and control systems researcher whose work has made significant contributions to the challenging problem of robotic contact dynamics and impact control. Specializing in adaptive and neural network-based control strategies, Dupree has focused primarily on developing robust controllers for robotic systems as they transition from free motion into contact with uncertain environments — a technically demanding problem with wide-ranging practical implications. Dupree's most influential work, "Adaptive Lyapunov-Based Control of a Robot and Mass–Spring System Undergoing an Impact Collision" (2008, 64 citations), established a rigorous theoretical framework using Lyapunov stability methods to manage the complex dynamics that arise during impact collisions, including rapid energy dissipation and high transient stresses. Subsequent research extended these ideas to viscoelastic environments modeled with Hunt-Crossley and other nonlinear formulations, incorporating neural network compensation to handle system uncertainties that resist standard linear parameterization. Dupree's force-limiting adaptive controllers address critical safety concerns in human-robot interaction, rehabilitation robotics, and assistive technologies, where uncontrolled contact forces could cause harm or system instability. With a cumulative citation count exceeding 150 across nine key publications, Dupree's body of work represents a meaningful and enduring contribution to the fields of nonlinear control theory and intelligent robotics.
Research Focus
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