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About

K. Vollmann is a robotics researcher whose work centers on calibration-free stereo vision for manipulator control and the development of advanced robot simulation tools. Their major contributions include pioneering a method that enables robot manipulators to handle objects using an uncalibrated stereo vision system, allowing direct transition from image coordinates to motion commands—a significant step toward more flexible and adaptive automation. Vollmann further advanced this by introducing a 4-dimensional knowledge base that serves as long-term memory for uncalibrated vision-guided robots, enabling self-adaptation to changing conditions. In simulation, they developed parametric component approaches and realistic robot controller software instantiations, supporting the "Virtual Factory" concept. Their most-cited work, "Manipulator control by calibration-free stereo vision" (1996, 14 citations), and subsequent papers (2002, 13 citations; 2003, 9 citations) demonstrate steady impact. Vollmann’s research bridges practical industrial needs—particularly for non-automotive sectors—with innovative simulation and training methods, including computer-based training in virtual environments. Their contributions are especially notable for reducing dependency on calibration, making robotic systems more accessible and adaptable.