Papers
10
Total Citations
121
H-Index
5
About
Karl Kleinmann’s research lies at the intersection of industrial robotics, sensor fusion, and dexterous manipulation, with a focus on enabling robots to perform complex, adaptive tasks in real-world environments. His most influential work, “Multisensor Contour Following With Vision, Force, and Acceleration Sensors for an Industrial Robot” (53 citations), addresses a critical challenge in manufacturing: teaching robots to follow workpiece contours for tasks like sewing or cutting without time-consuming manual programming. By integrating multiple sensor modalities, Kleinmann’s approach allows robots to react dynamically to uncertainties, significantly improving efficiency and robustness. His earlier contributions to multifingered gripper control, including studies on the transition from precision to power grasps (21 citations) and modular solutions for peg-in-hole assembly (16 citations), have advanced the understanding of how dexterous hands can achieve both sensitivity and stability. Kleinmann’s work on predictive contour following using laser-camera-triangulation further demonstrates his commitment to practical, sensor-driven automation. With over 120 total citations, his research has shaped modern approaches to adaptive robotic manipulation, making him a key figure in the evolution of intelligent manufacturing systems.
Research Focus
Key Achievements
Top Papers
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- 4Predictive robotic contour following using laser-camera-triangulation11 citations · 2011
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- 6Filtering and Corner Detection in Predictive Robotic Contour Following4 citations · 2012
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