Thomas Schmiedel
Papers
3
Total Citations
117
H-Index
3
About
Thomas Schmiedel is a robotics researcher whose work bridges assistive healthcare and 3D perception. His most impactful contribution is the **IRON** keypoint detector and descriptor, introduced in a 2015 paper (42 citations), which enables high-speed, high-accuracy alignment of 3D depth maps. Crucially, IRON operates on **Normal Distribution Transforms (NDT)** rather than raw point clouds, offering a robust and efficient alternative for robot localization and mapping. This work has become a reference point for researchers seeking fast, reliable NDT-map matching. Schmiedel’s applied research is equally notable. He led the development of **ROREAS**, a robotic coach for walking and orientation training in post-stroke rehabilitation. Evaluated in field trials (2016, 70 citations), this prototype demonstrated how mobile robots can deliver structured, repetitive therapy, directly addressing a critical need in clinical recovery. He also tackled home safety with a **fast fallen-person detection system** (2017) that uses 3D NDT data to enable a mobile robot to robustly identify and respond to emergency falls. Through these works, Schmiedel has shown how advanced 3D perception can be translated into practical, life-improving robotic systems for healthcare and assisted living.
Research Focus
Key Achievements
Top Papers
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