Papers

2

Total Citations

7

H-Index

2

About

Abdelwaheb Hafs is a rising researcher at the intersection of robotics, control theory, and human-robot interaction, with a core focus on developing intelligent exoskeletons and assistive robotic systems. His work pioneers the application of **differential game theory** and **model predictive control** to create personalized, intuitive physical assistance. Hafs’s major contribution lies in formalizing human-robot collaboration as a finite-horizon inverse differential game, allowing exoskeletons to infer a user’s motor goals and adaptively share the effort required for trajectory-tracking tasks—a significant leap from rigid, pre-programmed assistance. His most cited work (2024, 4 citations) introduces this framework for wrist exoskeletons, while his 2025 paper (3 citations) extends it to **model predictive game control** for targeted interactive assistance in physical training and manufacturing. Though early in his career, Hafs’s novel approach—explicitly modeling the user’s future control decisions—addresses a critical limitation in current assistive systems, promising safer, more responsive, and truly collaborative robots. His research is poised to shape next-generation rehabilitation and industrial exoskeletons.

Research Focus

Key Achievements

2
H-Index
2
Papers
7
Total Citations
4
Avg Citations/Paper
🏆 Most Cited Paper
A Finite-Horizon Inverse Differential Game Approach for Optimal Trajectory-Tracking Assistance with a Wrist Exoskeleton
4 citations · 2024
📈 Most Prolific Year: 2024 (1 Papers)
🤝 Key Collaborators: 5
🏛 Institutions: Complexité, Innovation et Activités Motrices et Sportives, Université Paris-Saclay

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago