基于物理人机交互的智能助行器实时控制研究

摘要

针对大多数助行器没有集中研究传感器接口采集信号的问题以及缺乏对人机交互过程中主要参数的分析,提出一种运动辅助和监控系统援助的助行器(MAMAW),其主要目的是改进助行器的安全性和稳定性.首先,控制杆快速提取用户运动指令,由于这些信号中存在一种高频率信号分量,所以使用Benedict-Bordner g-h滤波器衰减这些高频分量;然后,分类交互信号并且通过模糊逻辑控制器将信号转换成运动指令;最后,提出的助行器考虑了使用过程中可能存在的跌倒情况,所以将安全模块的输出优先级提到最高,可直接使助行器运动或停止.实验结果表明提出的助行器能够按照用户期望方向平稳安全运行,且没有发生碰撞,完美地矫正了获取的数据并推理出了用户的指令意图;另外控制策略的计算量低且响应迅速.%Concerning that most aid walkers do not focus on the signal acquisition problem of sensor interface and lacking analysis of the main parameters in the process of man-machine interaction,this paper proposed a mobility assistance and monitoring aid walker(MAMAW),whose aim was to improve the safety and stability of aid walker.Firstly,it used control bars to extract the users' motion commands quickly.These signals existed a higher frequency component that was attenuated by a Benedict-Bordner g-h filter.Then,it classified the resulting interaction signals and converted them into motion commands through a fuzzy logic controller.Finally,the proposed aid walker considered the possible fall situation.So the priority of the output of security module was set to highest,and this could make the aid walker run or stop.The experimental results show that the proposed aid walker can operate smoothly and safely according to the users' desired directions with no collision,which perfectly correct the acquired data and infer the users' instruction intention.In addition,the calculation of control strategy is low and the response is fast.