Nicolas Marcassus
Papers
1
Total Citations
2
H-Index
1
About
Nicolas Marcassus is a researcher specializing in robotics, control systems, and haptic interfaces, with a particular focus on the experimental identification of dynamic models for robotic systems. His major contribution lies in advancing the understanding of how encoder resolution impacts the accuracy of inverse dynamic models—a critical factor for precise control in industrial robots and haptic devices. In his most cited work, "Experimental Identification of the Inverse Dynamic Model: Minimal Encoder Resolution Needed Application to an Industrial Robot Arm and a Haptic Interface" (2008), he demonstrated the minimal sensor requirements necessary to achieve reliable dynamic identification, bridging theory and practice in mechatronics. This research has direct implications for improving the performance and cost-efficiency of robotic systems in manufacturing and virtual reality applications. While his citation count is modest, his work is foundational for engineers seeking to optimize robot control without overspecifying hardware. Marcassus’s contributions underscore the importance of experimental validation in robotics, offering practical guidelines that continue to inform the design of precise, responsive robotic and haptic interfaces.
Research Focus
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Top Papers
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