Milad Ghorbani
Papers
1
Total Citations
2
H-Index
1
About
Milad Ghorbani is a robotics researcher whose work centers on humanoid robot control, particularly push recovery and balance maintenance—critical challenges for enabling robots to operate safely in human environments. His most cited paper, an experimental study on a learning-based approach for push recovery in the NAO humanoid robot, introduces a novel method for push detection using force-sensitive resistors (FSRs). This work addresses the fundamental problem of keeping humanoid robots stable during dynamic interactions, a prerequisite for tasks like imitation learning and real-world deployment. While his citation count is still emerging, Ghorbani’s research contributes to the growing field of adaptive robot locomotion, where machine learning techniques are applied to enhance robustness against external disturbances. His focus on practical, sensor-driven solutions for the widely used NAO platform makes his findings valuable for researchers working on affordable, accessible humanoid systems. As the demand for responsive, balance-capable robots increases in areas from service robotics to rehabilitation, Ghorbani’s foundational work on push recovery offers a stepping stone toward more resilient autonomous agents.
Research Focus
Key Achievements
Top Papers
- 1