Craig Birkhimer

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About

Craig Birkhimer is a researcher whose work sits at the intersection of precision robotics and human-robot collaboration, with a particular focus on industrial assembly. His most significant contribution is in the field of robot calibration, where he developed a method using a laser-based coordinate measuring system to achieve highly accurate absolute positioning for a Motoman P8 robot. This work, published in 2002 and cited 75 times, was notable for its use of a calibration template that was unconstrained by traditional fixtures, allowing for greater flexibility and precision in measurement. Birkhimer also made early and important strides in programming by demonstration, a key area of robotics research. He advocated for encoding human assembly skills using virtual impedance and virtual attractor trajectories, allowing robotic systems to learn from human operators by recognizing events and switching between atomic behaviors. This approach, detailed in his 2004 paper (12 citations), aimed to bridge the gap between human dexterity and robotic automation. While his 2005 work on extracting human strategies for assembly was less cited, it tackled the fundamental challenge of quantitatively analyzing human data to transfer assembly strategies to robots—a problem that remains central to modern robotics research.