Milad Shafiee
Papers
1
Total Citations
2
H-Index
1
About
Milad Shafiee is a robotics researcher specializing in humanoid robot locomotion, motion planning, and balance control. His work focuses on developing computationally efficient algorithms that enable bipedal robots to walk stably and recover from external disturbances in real time — a critical challenge in bringing humanoid robots into dynamic, unpredictable environments. His most notable contribution to date is a methodology for online Divergent-Component-of-Motion (DCM) trajectory generation, designed specifically for torque-controlled humanoid robots. This work addresses the practical challenge of push recovery by integrating a step adapter into existing control architectures, allowing robots to dynamically adjust their footstep plans in response to unexpected perturbations. The approach stands out for its computational efficiency, making it viable for real-time deployment on physical robotic systems. While still an emerging researcher with his 2019 paper accumulating 2 citations, Shafiee's research tackles foundational problems at the intersection of trajectory optimization and whole-body control that are essential for advancing humanoid mobility. His contributions reflect a growing body of work aimed at making legged robots more robust, adaptive, and deployable in real-world scenarios — a pursuit central to the future of autonomous robotics.
Research Focus
Key Achievements
Top Papers
- 1