Safa Bouhajar
Papers
1
Total Citations
20
H-Index
1
About
Safa Bouhajar is a robotics researcher whose work centers on humanoid locomotion, trajectory generation, and predictive control systems. Her most-cited paper, “Trajectory Generation using Predictive PID Control for Stable Walking Humanoid Robot” (2015, 20 citations), introduces a refined approach to stabilizing bipedal walking by integrating predictive control strategies with PID controllers. This work builds on foundational theories by Katayama and Kajita, offering a practical method for calculating the center of mass trajectory to enhance walking stability. Bouhajar’s contributions address a core challenge in humanoid robotics—achieving smooth, adaptive motion in dynamic environments. While her citation count reflects a focused, emerging impact, her research bridges classical control theory with modern robotic applications, providing a framework that can be extended to real-time gait adaptation. Her work is particularly valuable for students and researchers exploring model-based control for legged robots, offering a clear example of how predictive PID can improve trajectory planning. Bouhajar’s efforts contribute to the broader goal of making humanoid robots more reliable and autonomous in real-world settings.
Research Focus
Key Achievements
Top Papers
- 1