Jens T. Thielemann
Papers
6
Total Citations
80
H-Index
4
About
Jens T. Thielemann’s research lies at the intersection of robotics, 3D computer vision, and autonomous navigation, with a strong emphasis on solving real-world industrial challenges. His most impactful work, “Pipeline landmark detection for autonomous robot navigation using time-of-flight imagery” (41 citations), pioneered the use of time-of-flight (TOF) cameras for detecting junctions, bends, and obstacles in cramped pipeline environments—a critical capability for autonomous inspection robots in oil and gas infrastructure. He extended this foundation with a robust 3D object detection and pose estimation method for remote maintenance operations on unmanned oil platforms, and developed the 3DMaMa algorithm for random bin picking in factory automation, enabling robots to locate and grasp arbitrarily oriented parts. More recently, Thielemann has ventured into underwater robotics, investigating light transport in turbid water to enable high-quality 3D imaging for subsea operations. His work on a foveating 3D laser scanner, inspired by the human eye, demonstrates a commitment to biologically inspired sensing for rapid, relevant data acquisition. With a career spanning autonomous navigation, industrial manipulation, and underwater imaging, Thielemann’s contributions have directly advanced the practicality of 3D sensing in harsh, unstructured environments.
Research Focus
Key Achievements
Top Papers
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- 4Light transport in turbid water for 3D underwater imaging6 citations · 2024
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