Erind Ujkani

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About

Erind Ujkani is a robotics researcher whose work focuses on the intersection of 3D perception, industrial automation, and human-robot collaboration. His key research areas include multi-sensor calibration, large-scale 3D environment mapping, and real-time safety systems for industrial robot cells. Ujkani’s most notable contribution is a novel procedure for visual marker-guided point cloud registration, which enables accurate calibration of multiple 3D sensors—such as the Kinect v2—in expansive industrial settings. This work, published in 2018, has garnered 12 citations and provides a benchmark for accuracy analysis in large robot cells. Expanding on this, his 2018 paper on distributed static 3D sensor nodes (11 citations) introduces a system architecture for mapping and real-time monitoring of environments up to 10 m × 15 m × 5 m, using six ceiling-mounted nodes with embedded computing. Additionally, his 2017 work on real-time human collision detection (6 citations) integrates ROS and the Point Cloud Library to trigger safety responses based on human motion, combining depth fields from multiple cameras. Together, these contributions advance the safety and efficiency of human-robot interaction in industrial settings, making Ujkani a key figure in the development of scalable, sensor-rich robotic environments.