Papers
15
Total Citations
606
H-Index
10
About
Sven Lilge is a leading robotics researcher whose work sits at the intersection of continuum robotics, robot modeling, and advanced kinematics. He has made foundational contributions to understanding and advancing tendon-driven and parallel continuum robots — flexible, compliant robotic systems with transformative potential in minimally invasive surgery, inspection, and other confined-space applications. Lilge's most influential work, "How to Model Tendon-Driven Continuum Robots and Benchmark Modelling Performance" (2021, 192 citations), has become an essential reference in the field, providing the community with a comprehensive, systematic framework for comparing modeling methodologies — a resource researchers had long needed. This benchmarking contribution is complemented by his early comparative study (2019, 90 citations) demonstrating rigorous empirical evaluation of modeling approaches for extensible continuum segments. Beyond modeling, Lilge has pioneered parallel continuum robot architectures, authoring both foundational design papers and a comprehensive survey (2024, 36 citations) that maps this emerging subfield. His work on Gaussian process regression for state estimation (2022, 47 citations) and learning-based inverse kinematics further demonstrates his command of data-driven methods. With over 570 cumulative citations, Lilge's research is shaping the theoretical and practical foundations of next-generation flexible robotics.
Research Focus
Key Achievements
Top Papers
- 1How to Model Tendon-Driven Continuum Robots and Benchmark Modelling Performance192 citations · 2021
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- 3Continuum robot state estimation using Gaussian process regression on SE(3)47 citations · 2022
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- 7Kinetostatic Modeling of Tendon-Driven Parallel Continuum Robots37 citations · 2022
- 8Parallel-Continuum Robots: A Survey36 citations · 2024
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