封面图片,第五卷,第三期,2025年9月

IF 3.6 Q1 ENGINEERING, MECHANICAL
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引用次数: 0

摘要

封面说明:使用基于rl的阻抗控制和数字孪生驱动的机器人支架进行脊柱侧凸康复:青少年特发性脊柱侧凸(AIS)通常使用传统支架进行治疗,传统支架仅依赖被动带张紧,缺乏智能控制策略。本研究提出了一种基于强化学习的基于位置的机器人支架阻抗控制(RLPIC)方法,以实现主动的人-机器人交互。为了安全地模拟和训练控制系统,开发了一种新的五维三层数字孪生(DT)模型,集成了物理建模、数字建模、双向交互和优化,并通过基于神经网络的参数估计器进行了增强。数值模拟和实时实验验证了DT和RLPIC框架,证明了AIS处理中改进的跟踪和交互性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Cover Image, Volume 5, Number 3, September 2025

Cover Image, Volume 5, Number 3, September 2025

Cover Caption: Scoliosis Rehabilitation with a Robotic Brace Powered by RL-based Impedance Control and Digital Twin: Adolescent Idiopathic Scoliosis (AIS) is commonly treated with traditional braces that rely solely on passive strap tensioning, lacking intelligent control strategies. This study proposes a reinforcement learning-based position-based impedance control (RLPIC) method for robotic braces to enable active human–robot interaction. To safely simulate and train the control system, a novel five-dimensional, three-layer digital twin (DT) model is developed, integrating physical modeling, digital modeling, bidirectional interaction, and optimization, enhanced by a neural network-based parameter estimator. Both numerical simulations and real-time experiments validate the DT and RLPIC framework, demonstrating improved tracking and interaction performance in AIS treatment.

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