Papers
11
Total Citations
294
H-Index
7
About
Didier Devaurs is a leading researcher at the intersection of robotics and structural biology, renowned for developing sampling-based motion planning algorithms that bridge these two fields. His most significant contribution is the Transition-based RRT (T-RRT), a groundbreaking algorithm for navigating complex cost spaces that has accumulated over 83 citations. Devaurs has extended this work through multi-tree approaches and low-dimensional projection techniques, enabling efficient exploration of high-dimensional conformational spaces in both robotic manipulation and biomolecular systems. His research has yielded practical tools like MoMA-LigPath, a web server for simulating protein-ligand unbinding (46 citations), and has advanced the characterization of peptide energy landscapes using stochastic algorithms. With over 290 total citations across his most-cited papers, Devaurs has demonstrated remarkable impact in applying robotics-inspired methods to molecular caging prediction, protein conformational sampling, and aerial manipulation with towed-cable systems. His work continues to influence both autonomous robotics and computational structural biology, making him a pivotal figure in the growing field of robotics-inspired computational biology.
Research Focus
Key Achievements
Top Papers
- 1Enhancing the transition-based RRT to deal with complex cost spaces83 citations · 2013
- 2Motion Planning for 6-D Manipulation with Aerial Towed-cable Systems65 citations · 2013
- 3MoMA-LigPath: a web server to simulate protein–ligand unbinding46 citations · 2013
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- 6A Robotics-Inspired Screening Algorithm for Molecular Caging Prediction8 citations · 2020
- 7Improving protein conformational sampling by using guiding projections7 citations · 2015
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- 9A multi-tree approach to compute transition paths on energy landscapes5 citations · 2013
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