Steven Hoedt
Papers
1
Total Citations
9
H-Index
1
About
Steven Hoedt is a researcher whose work sits at the intersection of robotics, automation, and manufacturing optimization. His primary focus is on enhancing the efficiency and predictability of robotic systems, particularly in assembly cells. His most-cited paper, "Spline-based trajectory generation to estimate execution time in a robotic assembly cell" (2022, 9 citations), introduces a novel method for generating smooth, time-efficient robot paths using spline interpolation. This contribution is critical for reducing cycle times and improving production throughput in automated environments. By enabling accurate estimation of execution times, Hoedt’s work directly supports smarter scheduling and resource allocation in industrial settings. Though his citation count is modest, his research addresses a practical bottleneck in robotics—trajectory planning—with clear applications in smart manufacturing. His achievements demonstrate a strong commitment to bridging theoretical control methods with real-world automation challenges, making his work valuable for engineers and researchers seeking to optimize robotic performance in dynamic assembly tasks.
Research Focus
Key Achievements
Top Papers
- 1