当前位置: X-MOL 学术Front. Neurorobotics › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Exoskeleton Active Walking Assistance Control Framework Based on Frequency Adaptive Dynamics Movement Primitives
Frontiers in Neurorobotics ( IF 2.6 ) Pub Date : 2021-04-21 , DOI: 10.3389/fnbot.2021.672582
Shiyin Qiu , Wei Guo , Fusheng Zha , Jing Deng , Xin Wang

This paper introduces a novel exoskeleton active walking assistance control framework based on frequency adaptive dynamics movement primitives (FADMPs). The FADMPs proposed in this paper is an online learning and prediction algorithm which is able to online estimate the fundamental frequency of human joint trajectory, learn the shape of joint trajectory and predict the future joint trajectory during walking. The proposed active walking assistance control framework based on FADMPs is a model-based controller which relies on the human joint torque estimation. The assistance torque provided by exoskeleton is estimated by human lower limb inverse dynamics model which is sensitive to the noise in the joint motion trajectory. To estimate a smooth joint torque profile, the joint motion trajectory must be filtered first by a lowpass filter. However, lowpass filter will introduce an inevitable phase delay in the filtered trajectory. Both simulations and experiments in this paper show that the phase delay has a significant effect on the performance of exoskeleton active assistance. The active assistant control framework based on FADMPs aims at improving the performance of active assistance control by compensating the phase delay. Both simulations and experiments on active walking assistance control show that the performance of active assistance control can be further improved when the phase delay in the filtered trajectory is compensated by FADMPs.

中文翻译:

基于频率自适应动力学运动原语的外骨骼主动步行辅助控制框架

本文介绍了一种基于频率自适应动力学运动原语(FADMP)的新型外骨骼主动步行辅助控制框架。本文提出的FADMP是一种在线学习和预测算法,能够在线估计人体关节轨迹的基本频率,学习关节轨迹的形状并预测步行过程中未来的关节轨迹。所提出的基于FADMP的主动步行辅助控制框架是基于模型的控制器,其依赖于人体关节扭矩估计。外骨骼提供的辅助扭矩由人体下肢逆动力学模型估算,该模型对关节运动轨迹中的噪声敏感。为了估算平滑的关节扭矩曲线,必须先通过低通滤波器对关节运动轨迹进行滤波。然而,低通滤波器将在滤波后的轨迹中引入不可避免的相位延迟。本文的仿真和实验均表明,相位延迟对外骨骼主动辅助的性能有重大影响。基于FADMP的主动辅助控制框架旨在通过补偿相位延迟来提高主动辅助控制的性能。对主动步行辅助控制的仿真和实验均表明,当通过FADMP补偿滤波轨迹中的相位延迟时,可以进一步改善主动辅助控制的性能。基于FADMP的主动辅助控制框架旨在通过补偿相位延迟来提高主动辅助控制的性能。对主动步行辅助控制的仿真和实验均表明,当通过FADMP补偿滤波轨迹中的相位延迟时,可以进一步改善主动辅助控制的性能。基于FADMP的主动辅助控制框架旨在通过补偿相位延迟来提高主动辅助控制的性能。对主动步行辅助控制的仿真和实验均表明,当通过FADMP补偿滤波轨迹中的相位延迟时,可以进一步改善主动辅助控制的性能。
更新日期:2021-04-21
down
wechat
bug