Frederik Hagelskjar
Papers
3
Total Citations
30
H-Index
3
About
Frederik Hagelskjar is a robotics researcher whose work sits at the intersection of computer vision, industrial automation, and robotic manipulation. His research focuses primarily on visual pose estimation, gripper design optimization, and the practical deployment of vision-guided robotic systems in real-world manufacturing environments. Hagelskjar has made notable contributions to simplifying and accelerating the setup of precise robotic workcells — a longstanding challenge in industrial automation — through the development of spatially constrained pose estimation methods that deliver high accuracy without demanding excessive configuration overhead. His most cited work, "Using Spatial Constraints for Fast Set-up of Precise Pose Estimation in an Industrial Setting" (2019, 18 citations), demonstrates how carefully designed geometric constraints can dramatically streamline deployment workflows. His 2019 paper on combined optimization of gripper finger design and pose estimation processes (9 citations) reflects his broader ambition to co-design mechanical and computational elements for improved system reliability. Earlier work on dynamic simulation for gripper optimization under pose uncertainty further underscores his commitment to robust, adaptable robotic solutions. Hagelskjar's research is particularly valuable for engineers and researchers seeking to bridge the gap between theoretical robotics and scalable industrial implementation.
Research Focus
Key Achievements
Top Papers
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