About

Damien Chablat is a prominent robotics researcher whose work spans parallel robot kinematics, stiffness modeling, compliance error compensation, and human-robot collaboration. Based at a leading French research institution, Chablat has made foundational contributions to understanding the mechanical behavior and design optimization of complex robotic systems, particularly parallel manipulators. His most cited work focuses on elasto-static parameter identification and stiffness modeling of robotic manipulators, with his 2013 and 2018 papers accumulating over 130 and 114 citations respectively, establishing him as a key authority in structural rigidity analysis for robotics. His in-depth kinematic analysis of the agile eye — a spherical parallel robot with unique orthogonal joint architecture — has become a reference study in parallel wrist design, earning 81 citations. Complementing this, his research on compliance error compensation in parallel robots addresses critical precision challenges in industrial applications. Beyond classical kinematics, Chablat has explored multimode parallel robots, Delta-like robot families, and optimal machine tool design for high-speed machining. His 2017 work on industrial human-robot coexistence security systems reflects a broader commitment to practical, safety-conscious robotics deployment. With over 600 cumulative citations across diverse robotic domains, Chablat represents a versatile and impactful voice in modern robotics research.

Research Focus

Key Achievements

20
H-Index
112
Papers
1,535
Total Citations
14
Avg Citations/Paper
🏆 Most Cited Paper
CAD-based approach for identification of elasto-static parameters of robotic manipulators
130 citations · 2013
📈 Most Prolific Year: 2018 (11 Papers)
🤝 Key Collaborators: 117
🏛 Institutions: Centre National de la Recherche Scientifique, Laboratoire de Thermique et Energie de Nantes, École Centrale de Nantes, Université de technologie de belfort-montbéliard, Vivant (United States), Laboratoire des Sciences du Numérique de Nantes

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
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