Multicontact Safety-Critical Planning and Adaptive Neural Control of a Soft Exosuit Over Different Terrains

Many previous works on wearable soft exosuits have primarily focused on assisting human motion, while overlooking safety concerns during movement. This article introduces a novel single-motor, altering bi-directional transfer soft exosuit based on impedance optimization and adaptive neural control, which provides assistance to the lower limbs using Bowden cables. This innovative soft exosuit integrates control barrier functions into the impedance optimization, allowing multiple safety constraints to be considered simultaneously, enabling the system to adaptively learn the impedance of the human ankle joint by analyzing the measured interaction forces at the ankle joint, so that the updated reference trajectories comply with safety requirements. To effectively track the updated reference trajectories, we have introduced an adaptive neural controller based on the integral barrier Lyapunov function. This controller is designed to perform the control task under strict safety constraints. The stability of this control approach is meticulously demonstrated through extensive Lyapunov analysis. In contrast to traditional soft exosuits designed purely for assistance, the key advantage of this technology is its ability to adapt to different terrains while ensuring the safety of human movement during assistance. Through experimental testing, we obtain average tracking errors of 0.0062, 0.0062, and 0.0063 rad for flat, grass, and gravel surfaces, respectively, demonstrating the effectiveness of the proposed strategy.

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Institutions

Publication Details

Journal
IEEE Transactions on Cybernetics
Published
2025-03-26
DOI
https://doi.org/10.1109/tcyb.2025.3550746
Citations
2
Primary Topic
Robotic Mechanisms and Dynamics
Type
article
Field-Weighted Citation Impact
2.43

Funders

Controls
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article

Multicontact Safety-Critical Planning and Adaptive Neural Control of a Soft Exosuit Over Different Terrains

Guoxin Li, Zhijun Li, Liangrui Xu, Wei Yang
2 citations
IEEE Transactions on Cybernetics
Robotic Mechanisms and Dynamics
2.43
article

Multicontact Safety-Critical Planning and Adaptive Neural Control of a Soft Exosuit Over Different Terrains

Guoxin Li, Zhijun Li, Liangrui Xu, Wei Yang
article en
2 citations

Abstract

Many previous works on wearable soft exosuits have primarily focused on assisting human motion, while overlooking safety concerns during movement. This article introduces a novel single-motor, altering bi-directional transfer soft exosuit based on impedance optimization and adaptive neural control, which provides assistance to the lower limbs using Bowden cables. This innovative soft exosuit integrates control barrier functions into the impedance optimization, allowing multiple safety constraints to be considered simultaneously, enabling the system to adaptively learn the impedance of the human ankle joint by analyzing the measured interaction forces at the ankle joint, so that the updated reference trajectories comply with safety requirements. To effectively track the updated reference trajectories, we have introduced an adaptive neural controller based on the integral barrier Lyapunov function. This controller is designed to perform the control task under strict safety constraints. The stability of this control approach is meticulously demonstrated through extensive Lyapunov analysis. In contrast to traditional soft exosuits designed purely for assistance, the key advantage of this technology is its ability to adapt to different terrains while ensuring the safety of human movement during assistance. Through experimental testing, we obtain average tracking errors of 0.0062, 0.0062, and 0.0063 rad for flat, grass, and gravel surfaces, respectively, demonstrating the effectiveness of the proposed strategy.

IEEE Transactions on CyberneticsVol. 55(5)
University of Science and Technology of China (CN)
National Natural Science Foundation of China, China Postdoctoral Science Foundation, Natural Science Foundation of Anhui Province, National Key Research and Development Program of China
Climate action
Openalex Percentile: Top 13%
Robotic Mechanisms and Dynamics
2.43
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