Study on Sensing Information Forecasting of Wearable Power Assist Walking Legs Based on Time Series Analysis

Abstract

The Wearable Power Assist Walking Legs(PAWL) is an autonomous exoskeleton robot,which requires the actuators can response rapidly according to the force information and the angle information from the sensing system.In order to improve the dynamic response of the whole system,we propose a novel forecasting algorithm based on time series analysis.Because of the requirement of the real-time,the forecasting algorithm is designed for utilizing on-line.In the end,some correlative experiments have been made and the results illustrate the validity and effectiveness of the algorithm.