Alexandre Janot
Office National d'Études et de Recherches Aérospatiales, Institut Superieur de l'Aeronautique et de l'Espace (ISAE-SUPAERO), Commissariat à l'Énergie Atomique et aux Énergies Alternatives, Université Fédérale de Toulouse Midi-Pyrénées, Haption (France), Laboratoire d'Intégration des Systèmes et des Technologies, Université Paris-Saclay
Papers
54
Total Citations
1,018
H-Index
15
About
Alexandre Janot is a prominent French robotics researcher whose work has fundamentally advanced the field of robot dynamic identification — the science of accurately determining the physical parameters that govern how robots move and interact with their environment. Working primarily within industrial and collaborative robotics contexts, Janot has made landmark contributions to parameter identification methodology, developing and refining techniques that allow engineers to build more precise dynamic models for model-based control and simulation. His most influential contribution, a closed-loop output error method published in 2012 (185 citations), redefined how robot dynamics are identified offline by moving beyond traditional inverse dynamic approaches. Complementing this, his development of instrumental variable techniques (126 citations) addressed critical noise and bias challenges inherent in standard least-squares identification, substantially improving robustness for industrial applications. His earlier DIDIM method (2008) demonstrated that accurate identification could be achieved using torque data alone — a significant practical breakthrough. Janot's 2021 survey on inertial parameter identification (95 citations) stands as a comprehensive reference for the field, further distinguished by the release of BIRDy, an open-source MATLAB benchmarking toolbox that democratizes access to cutting-edge identification methods. His applied work on the Kuka LightWeight Robot has provided the research community with previously unavailable validated dynamic models, cementing his reputation as both a rigorous theorist and a practitioner of real-world impact.
Research Focus
Key Achievements
Top Papers
- 1
- 2A Generic Instrumental Variable Approach for Industrial Robot Identification126 citations · 2014
- 3Inertial Parameter Identification in Robotics: A Survey95 citations · 2021
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- 9An instrumental variable approach for rigid industrial robots identification33 citations · 2014
- 10A revised Durbin-Wu-Hausman test for industrial robot identification27 citations · 2016