Fadwa El Aswad

About

Fadwa El Aswad is a researcher at the intersection of human-robot interaction and intelligent manufacturing, with a focus on developing intuitive control systems for collaborative robots (cobots). Her most cited work, "Image Generation for 2D-CNN Using Time-Series Signal Features from Foot Gesture Applied to Select Cobot Operating Mode" (2021, 13 citations), introduces a novel approach that transforms foot gesture signals into image representations for convolutional neural network classification. This innovation enables workers to control cobots hands-free, allowing the robot to function as a "third arm" during assembly tasks—a significant contribution to reducing physical burden in manufacturing environments. By designing more natural and intuitive control modalities, El Aswad's research addresses critical challenges in human-robot collaboration, particularly in industrial settings where workers need to maintain manual dexterity while commanding robotic assistance. Her work represents an important step toward safer, more efficient human-robot teamwork, with potential applications spanning from automotive assembly to precision manufacturing.

Research Focus

Key Achievements

Top Papers

1. 1
   Image Generation for 2D-CNN Using Time-Series Signal Features from Foot Gesture Applied to Select Cobot Operating Mode

   13 citations · 2021

Key Collaborators

Contact & Links