Papers

5

Total Citations

42

H-Index

3

About

A. Mounir Boudali is a researcher specializing in the control and modeling of dynamic walking robots, with a focus on underactuated systems and soft robotics. His major contributions include developing invariant funnels for stable walking, using sum-of-squares verification to guarantee continued locomotion from a set of initial conditions—a key advancement for reliable bipedal robots. He also pioneered phase-indexed iterative learning control (ILC), enabling robots to refine their gait cycles despite non-periodic iterations, which has been cited 15 times. Boudali’s work extends to soft robotics, where he modeled EGaIn-based strain sensors for proprioceptive sensing, addressing the lack of accurate mathematical models for strain estimation—a critical step for soft robot control. He also designed an open-platform compass-gait bipedal robot for dynamic walking research, promoting low-cost experimentation. With over 42 citations across his top papers, Boudali’s research bridges theoretical control methods and practical robotic applications, including system identification for bipedal locomotion in both robots and humans, contributing to advancements in exoskeletons and prosthetics for gait rehabilitation.

Research Focus

Key Achievements

3
H-Index
5
Papers
42
Total Citations
8
Avg Citations/Paper
🏆 Most Cited Paper
Invariant funnels for underactuated dynamic walking robots: New phase variable and experimental validation
17 citations · 2017
📈 Most Prolific Year: 2017 (2 Papers)
🤝 Key Collaborators: 8
🏛 Institutions: The University of Sydney, Australian Centre for Robotic Vision

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 16 days ago