About

A. Jubien is a robotics researcher whose work has made significant contributions to the dynamic identification and calibration of robotic manipulators, with a particular focus on industrial and lightweight robots. Operating primarily in the early-to-mid 2010s, Jubien developed and refined sophisticated methods for characterizing the dynamic parameters of complex robotic systems, most notably the Kuka LightWeight Robot (LWR), a platform widely adopted in research laboratories yet lacking a publicly available dynamic model. Jubien's comparative studies between identification techniques — including the CLOE and DIDIM methods — have provided the robotics community with valuable benchmarks for choosing appropriate modeling strategies (accumulating over 23 citations). Particularly impactful is the 2014 work on dynamic identification using motor torques and joint torque sensors, which has garnered 59 citations and remains a key reference in model-based robot control. Jubien also advanced joint stiffness identification for flexible manipulators, demonstrating that accurate parameter estimation can be achieved using only motor torque data, eliminating the need for complex sensor configurations. With contributions spanning force calibration, kinematics, and drive gain identification, Jubien's body of work continues to support researchers developing more precise, model-driven control strategies for modern robotic systems.

Research Focus

Key Achievements

9
H-Index
18
Papers
245
Total Citations
14
Avg Citations/Paper
🏆 Most Cited Paper
Dynamic identification of the Kuka LWR robot using motor torques and joint torque sensors data
59 citations · 2014
📈 Most Prolific Year: 2014 (6 Papers)
🤝 Key Collaborators: 8
🏛 Institutions: Nantes Université, Office National d'Études et de Recherches Aérospatiales, Laboratoire des Sciences du Numérique de Nantes, Laboratoire de Thermique et Energie de Nantes, Institut de Recherche en Informatique de Toulouse, Institut Superieur de l'Aeronautique et de l'Espace (ISAE-SUPAERO)

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago