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20192022
most citedPowered Prosthesis Locomotion on Varying Terrains: Model-Dependent Control with Real-Time Force Sensing

14 citations · 30 across the 6 of their papers we have counts for

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5 papers · 1 filter

cs.RO2022

Emulating Human Kinematic Behavior on Lower-Limb Prostheses via Multi-Contact Models and Force-Based Nonlinear Control

Rachel Gehlhar, Aaron D. Ames

Ankle push-off largely contributes to limb energy generation in human walking, leading to smoother and more efficient locomotion. Providing this net positive work to an amputee req…

cs.RO2021

Natural Multicontact Walking for Robotic Assistive Devices via Musculoskeletal Models and Hybrid Zero Dynamics

Kejun Li, Maegan Tucker, Rachel Gehlhar +2

Generating stable walking gaits that yield natural locomotion when executed on robotic-assistive devices is a challenging task that often requires hand-tuning by domain experts. Th…

cs.RO2021★ 14 cited

Powered Prosthesis Locomotion on Varying Terrains: Model-Dependent Control with Real-Time Force Sensing

Rachel Gehlhar, Je-han Yang, Aaron D. Ames

Lower-limb prosthesis wearers are more prone to falling than non-amputees. Powered prostheses can reduce this instability of passive prostheses. While shown to be more stable in pr…

cs.RO2020

Data-driven Characterization of Human Interaction for Model-based Control of Powered Prostheses

Rachel Gehlhar, Yuxiao Chen, Aaron D. Ames

This paper proposes a data-driven method for powered prosthesis control that achieves stable walking without the need for additional sensors on the human. The key idea is to extrac…

cs.RO2019★ 4 cited

Control of Separable Subsystems with Application to Prostheses

Rachel Gehlhar, Jenna Reher, Aaron D. Ames

Nonlinear control methodologies have successfully realized stable human-like walking on powered prostheses. However, these methods are typically restricted to model independent con…