摘要
在辅助行走或步行康复训练过程中,助行机器人在紧密跟随人体步态的基础上,准确识别异常行为是人机交互的重要研究内容。为此,提出一种兼具通用性、鲁棒性与便捷性的非接触式多模态步行意图识别方法,能够准确识别多种步态并柔顺地控制机器人运行。首先,分析了步行辅助机器人和步行康复训练机器人的结构、功能与运动学模型,建立了内嵌式机载步态信息检测系统,从而准确描述步态变化规律;其次,为有效解决标志点丢失问题,提出了一种新型的扩展集员滤波算法来精确估计膝关节角度;最后,通过引入用户步态信息,建立了一种基于步态补偿的柔性控制方法并进行了实验研究。实验表明,提出的算法能够在有效克服标记点丢失的情况下,准确识别交互过程中的正常步态,并柔顺地控制机器人运动,同时对跌倒和拖拽步态进行有效识别,识别率分别达到91.3%和89.3%。该非接触式步态意图识别方法可以应用于具有类似结构的助行器及其日常助行与康复训练场景。
During the process of assisted walking or gait rehabilitation training,it is essential to recognize abnormal behaviors accurately in human-computer interaction on the basis of following user′s gait closely.This article proposes a non-contact recognition method which has advantages of universality,robustness,and convenience for multimodal walking intention.It can control the robot flexibly and accurately recognize various gaits.Firstly,the structure,functions,and kinematics models of the walking assist robot and the gait rehabilitation training robot are introduced,and an embedded airborne gait recognition system is established.It can accurately describe the gait and changing rule.Secondly,to effectively solve the problem of mark point loss,a new extended set membership filter is proposed to estimate the knee angle.Finally,a compliance control method based on walking speed compensation is established by combining with gait information.Experimental results show that the proposed method could effectively overcome the loss of marker points,identify the normal gait accurately in the interaction process,and flexibly control the robot movement.Meanwhile,it can effectively recognize the falling and drag-to-drop gait.The recognition rates are 91.3%and 89.3%,respectively.The non-contact walking intention recognition method can be applied to walkers with similar structures and their daily walking assistance or rehabilitation training.
作者
赵东辉
王威
张紫涵
杨子豪
杨俊友
Zhao Donghui;Wang Wei;Zhang Zihan;Yang Zihao;Yang Junyou(School of Electrical Engineering,Shenyang University of Technology,Shenyang 110870,China)
出处
《仪器仪表学报》
EI
CAS
CSCD
北大核心
2022年第2期205-215,共11页
Chinese Journal of Scientific Instrument
基金
中央引导地方科技发展项目(2021JH6/10500216)
辽宁省自然科学基金(2021-BS-152)
辽宁省教育厅面上项目(LJKZ0124)资助
关键词
助行机器人
柔顺控制
拖拽步态
标记点丢失
非接触检测
walking aid robot
compliance control
drag-to-drop gait
marker point loss
non-contact recognition
