Papers
6
Total Citations
93
H-Index
4
About
Mohamed Elobaid is a leading researcher at the intersection of humanoid robotics, human-robot interaction, and whole-body control. His work centers on enabling robots to serve as immersive avatars for remote telepresence and to collaborate safely with humans in physical tasks. His most impactful contribution is the iCub3 avatar system, which enables fully immersive, remote embodiment of a humanoid robot—a breakthrough validated through extensive case studies and earning over 60 citations. Elobaid has also made significant advances in control theory, developing adaptive nonlinear centroidal Model Predictive Control (MPC) for robust legged locomotion and payload carrying, with stability guarantees for real-world deployment. His research on ergonomic human-robot collaboration introduces control approaches that monitor human partners to reduce physical strain during lifting. Additionally, his work on XBG (eXteroceptive Behaviour Generation) pioneers end-to-end imitation learning for autonomous social interaction. With multiple recent publications in top venues and a growing citation impact, Elobaid is shaping the future of humanoid robotics as both a practical tool for telepresence and a collaborative partner in industry and daily life.
Research Focus
Key Achievements
Top Papers
- 1
- 2A Control Approach for Human-Robot Ergonomic Payload Lifting12 citations · 2023
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- 6Remote telepresence over large distances via robot avatars: case studies2 citations · 2024