Carsten Reiners
Papers
1
Total Citations
4
H-Index
1
About
Carsten Reiners is a researcher whose work centers on the precise modeling and control of industrial robotic systems, with a particular emphasis on the identification of inertial parameters. His most-cited paper, "Frequency-Based Identification of the Inertial Parameters of an Industrial Robot" (2020), introduces a novel method for extracting critical dynamic properties of robots using frequency-domain analysis. This contribution is foundational for improving robot accuracy, safety, and energy efficiency in manufacturing and automation. Despite its recent publication, the work has already garnered 4 citations, signaling growing recognition among peers in robotics and control engineering. Reiners’ approach addresses a persistent challenge in robotics: the need for accurate dynamic models without disassembling the robot. By leveraging frequency-based techniques, his research enables more reliable simulation, trajectory planning, and adaptive control. His work is particularly valuable for students and engineers seeking to bridge the gap between theoretical dynamics and practical robot calibration. Reiners’ contributions are poised to influence the next generation of intelligent, self-tuning industrial robots, making his research a key reference for those advancing automation and robotic precision.
Research Focus
Key Achievements
Top Papers
- 1