C
Christophe Maufroy
Researcher at Fraunhofer Society
Publications - 26
Citations - 523
Christophe Maufroy is an academic researcher from Fraunhofer Society. The author has contributed to research in topics: Exoskeleton & Motion control. The author has an hindex of 10, co-authored 24 publications receiving 442 citations. Previous affiliations of Christophe Maufroy include University of Jena & University of Electro-Communications.
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Integration of posture and rhythmic motion controls in quadrupedal dynamic walking using phase modulations based on leg loading/unloading
TL;DR: The proposed general legged locomotion controller with the ability to integrate both posture and rhythmic motion controls and shift continuously from one control method to the other according to the walking speed enables low speed dynamic walking on uneven terrain with long cyclic period.
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2008 Special Issue: Towards a general neural controller for quadrupedal locomotion
TL;DR: The simulation of steady walking at 0.6 m/s of both the forelegs only and the hind legs only (with a supporting structure at the back and at the front respectively), achieved using the quadrupedal model is reported.
Journal ArticleDOI
Robust hopping based on virtual pendulum posture control.
Maziar Ahmad Sharbafi,Christophe Maufroy,Majid Nili Ahmadabadi,Mohammad Javad Yazdanpanah,Andre Seyfarth +4 more
TL;DR: A new control approach to achieve robust hopping against perturbations in the sagittal plane is presented, based on the virtual pendulum concept, and substantial enhancements with respect to stability, convergence speed and robustness against perturbed hopping and parameter changes are achieved.
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Concept and design of the biobiped1 robot for human-like walking and running
TL;DR: The design and implementation of the first of a planned series of biologically inspired, compliant, and musculoskeletal robots is presented, which aims to transfer versatile human locomotion abilities, namely running and later on walking, into one humanoid robot design.
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Leg-adjustment strategies for stable running in three dimensions.
TL;DR: The prediction of stable running based on movement-related leg-adjustment strategies indicates that both humans and robots may not require external targets directing the movement to run in three dimensions based on compliant leg function.