Lorena Gril
Papers
1
Total Citations
6
H-Index
1
About
Lorena Gril is a researcher at the forefront of human-robot interaction, with a primary focus on enhancing safety and collaboration in industrial robotic systems. Her work centers on developing predictive models that allow robots to anticipate human motion, thereby preventing hazardous situations before they occur. Gril’s most notable contribution is her tensor-based regression approach for human motion prediction, a novel methodology that improves the accuracy and efficiency of anticipating dynamic human movements in shared workspaces. This work, published in 2022, has already garnered 6 citations, reflecting its early impact on the field. By addressing a critical bottleneck in collaborative robotics—ensuring human safety without sacrificing productivity—Gril’s research has significant implications for the next generation of smart manufacturing environments. Her contributions are particularly relevant as industries increasingly adopt flexible, human-centric automation, positioning her as a rising voice in the development of safer, more intuitive robotic systems.
Research Focus
Key Achievements
Top Papers
- 1A Tensor‐based Regression Approach for Human Motion Prediction6 citations · 2022