Problem
Research questions and friction points this paper is trying to address.
pneumatic artificial muscles
soft exosuits
user intention
dynamic assistance
kinematic sensing
A Task-Agnostic Control Strategy for Dynamic Assistance with Pneumatically Actuated Soft Exosuits
🤖 AI Summary
本文提出了一种基于气动肌肉的软外骨骼控制策略，通过仅依赖运动学感知实现无需特定任务识别的动态辅助，有效减少了交互扭矩和肌肉激活。
📝 Abstract
Pneumatic artificial muscles have provided new opportunities to develop upper-extremity soft exosuits for reha- bilitation, augmentation, and assisted daily living. However, the complex dynamics and limited bandwidth of these actuators has made providing responsive assistance based on user intention a longstanding challenge. In this work, we present an inverse-plant control strategy for pneumatically actuated soft exosuits that only relies on kinematic sensing for task-agnostic and dynamic assistance during daily living. We model the human-robot system using a Hammerstein dynamic model, consisting of a Preisach hysteresis model and a linear time-invariant filter, to capture the static and dynamic behavior of the system. We personalize our model to each user using 140 s of data and approximate an inverse to integrate into our control loop. When evaluated on a test rig that emulated a soft assistive exosuit for the wrist, our controller reduced the interaction torque by up to 73% and the activation of key flexor and extensor muscles by up to 47% relative to the condition with no assistance for speeds ranging from 8°/s to 120°/s. Overall, this work presents a control strategy that can provide task-agnostic, dynamic assistance with pneumatically actuated soft exosuits without the need for physiological or force sensors to interpret user intention.
Innovation
Methods, ideas, or system contributions that make the work stand out.
inverse-plant control strategy
task-agnostic assistance
pneumatic actuation
Hammerstein dynamic model
kinematic sensing
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2024-10-10arXiv.orgCitations: 0
