About

David Corbel is a robotics researcher whose work has made significant contributions to the design, dynamics, and calibration of parallel kinematic machines (PKM), with a particular focus on high-speed pick-and-place applications. His most influential research investigates the role of actuation redundancy in dramatically enhancing the acceleration capabilities of parallel manipulators, most notably Delta and Par4-like robots. His two landmark papers from 2010—together accumulating nearly 110 citations—rigorously examine whether redundant actuation is a viable pathway to achieving extraordinary accelerations approaching 100G, providing dynamic models and practical insights that have shaped subsequent research in ultra-high-speed robotics. Corbel has also made notable strides in geometric calibration, developing improved methods to precisely characterize parallelogram-based parallel robots and applying laser tracker technology to the Par4 robot to enhance real-world positioning accuracy. His doctoral thesis further synthesized these threads, proposing a comprehensive framework balancing high dynamics with precision through geometric calibration, metrological redundancy, and kinematic redundancy strategies. His exploration of auto-calibrating mechanisms, such as the ARCHI robot, underscores his commitment to practical, self-improving robotic systems. Corbel's body of work remains a valuable reference for researchers and engineers advancing the frontiers of parallel robotics.

Research Focus

Key Achievements

6
H-Index
6
Papers
146
Total Citations
24
Avg Citations/Paper
🏆 Most Cited Paper
Actuation Redundancy as a Way to Improve the Acceleration Capabilities of 3T and 3T1R Pick-and-Place Parallel Manipulators
61 citations · 2010
📈 Most Prolific Year: 2010 (2 Papers)
🤝 Key Collaborators: 6
🏛 Institutions: Centre National de la Recherche Scientifique, Laboratoire d'Informatique, de Robotique et de Microélectronique de Montpellier, Université de Montpellier

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago