J. D. Keuning

Papers

Total Citations

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About

J. D. Keuning’s research lies at the intersection of robotics, control systems, and micro-manipulation, with a particular focus on imitation learning and magnetic actuation. Their most-cited work, “Image-based magnetic control of paramagnetic microparticles in water” (2011, 10 citations), introduces a novel approach to precisely manipulating microscopic particles using magnetic fields guided by visual feedback—a technique with promising applications in biomedical engineering and lab-on-a-chip technologies. Beyond this, Keuning has contributed to advancing Programming by Demonstration (imitation learning), where robots learn complex tasks from human demonstration. Notably, they have explored the often-overlooked role of force information in skill transfer, moving beyond purely kinematic models to capture the nuanced physical interactions required for tasks like assembly or manipulation. This work addresses a critical gap in robotic learning, enabling more dexterous and adaptive robot behavior. While their citation count reflects a focused, emerging impact, Keuning’s contributions are foundational for researchers working on intuitive human-robot interfaces and precise micro-robotic control.