Fredrik Bagge Carlson
Papers
8
Total Citations
113
H-Index
5
About
Fredrik Bagge Carlson is a leading researcher at the intersection of robotics, control theory, and machine learning, with a focus on enabling intelligent, adaptive behavior in physical systems. His work spans friction modeling, sensor calibration, and human-robot interaction, making significant contributions to both industrial automation and robot learning. Carlson’s highly cited 2015 paper on modeling position- and temperature-dependent friction phenomena (31 citations) introduced a novel approach using Radial Basis Function networks, while his work on eye-to-hand calibration (27 citations) provided a linear, iterative method for robotic perception. He also advanced lead-through programming (25 citations), enabling intuitive robot teaching without external sensors. His research on dynamical movement primitives (DMPs) and two-degree-of-freedom control (11 citations) has strengthened the framework for trajectory tracking and perturbation recovery. More recently, Carlson has tackled the challenges of robotic friction stir welding, developing seam-tracking control and force supervision. A notable achievement is his development of a generic robot library in the Julia programming language, bridging low-level motion guidance with high-level control interfaces. With over 100 total citations, Carlson’s work continues to shape the future of autonomous, sensor-driven robotic systems.
Research Focus
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