下肢外骨骼机器人意图识别算法研究  

Intention Recognition for Lower-Limb Exoskeleton

作　　者：陈启明[1] 黄瑞[1] CHEN Qi-ming;HUANG Rui(Center for Robotics, School of Automation Engineering, University of Electronic Science and Technology of China Chengdu 611731)

机构地区：[1]电子科技大学机器人研究中心,成都611731

出　　处：《电子科技大学学报》2018年第3期330-336,共7页Journal of University of Electronic Science and Technology of China

基　　金：国家自然科学基金(71201017);中央高校基本科研业务费(ZYGX2012J101)

摘　　要：下肢外骨骼机器人能让截瘫患者一定程度上恢复站立、行走等一些运动能力。其作为一种人机耦合的系统,人机交互接口(HMI)扮演着重要的角色。准确地获取穿戴者(截瘫患者)的运动意图,是下肢外骨骼机器人研发的主要挑战。针对当前意图识别主要采用手动阈值判断的方式,该文提出了一种利用机器人零力矩点(ZMP)特征,并基于支撑矢量机(online SVM)检测穿戴者运动意图的在线学习算法。最后在实际系统上完成该算法的验证。Lower limb exoskeletons enable paraplegics to regain some degree of locomotion ability, i.e., standing and walking. As a human machine system, the human machine interface（HMI） play an important role. The ideal lower limb exoskeleton for paralyzed people can move following the intention of pilot. To achieve it, many kinds of HMI systems are designed. However, for many exoskeletons, manual operation is still necessary for controlling the exoskeleton. In this paper, we designed and implemented an intention recognition method which is able to detect human motion intention. With the detected intention, exoskeleton can be controlled automatically as will of pilot. In this method, zero moment point（ZMP） is chosen as one of features of human intention and an online machine learning algorithm（online SVM） is used to learn intention online. Experiments in real systems show the effectiveness and advantages of our proposed method.

关 键 词：外骨骼 意图识别 机器学习 零力矩点 

分 类 号：TP24[自动化与计算机技术—检测技术与自动化装置]