Markus Wnuk
Papers
9
Total Citations
46
H-Index
4
About
Markus Wnuk is a robotics researcher whose work centers on one of industrial automation's most stubborn challenges: the robotic manipulation of deformable linear objects (DLOs) such as cables, hoses, and wire harnesses. His research spans perception, tracking, control, and simulation, making him a well-rounded contributor to a field that sits at the intersection of computer vision, physical modeling, and robot control. Wnuk's most influential contributions address the notoriously difficult problem of branched DLOs, which arise constantly in automotive production. His topology matching method (2023, 13 citations) introduced a principled approach to estimating correspondence between known wire harness structures and 3D stereo camera data, while his earlier tracking work (2021, 9 citations) enhanced structure-preserved registration to handle multi-branch geometries. His case study on wire harness installation localization (2023, 7 citations) demonstrates a commitment to grounding theoretical advances in real industrial settings. Earlier work explored simulation-based bin picking strategies (2017, 7 citations) and physics-driven trajectory control (2020–2021), reflecting a career-long effort to bridge computational modeling with practical robot deployment. With nearly 45 cumulative citations and a growing publication record, Wnuk represents an emerging voice in the automation of flexible object handling—a capability increasingly critical as manufacturing seeks to reduce reliance on manual assembly.
Research Focus
Key Achievements
Top Papers
- 1Topology Matching of Branched Deformable Linear Objects13 citations · 2023
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- 3Case Study on Localization for Robotic Wire Harness Installation7 citations · 2023
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- 7Harte Echtzeit für weiche Materialien2 citations · 2019
- 8
- 9Software architecture for deformable linear object manipulation1 citations · 2022