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Please use this identifier to cite or link to this item: http://hdl.handle.net/10119/12345

Title: Particle Filter Based Lower Limb Prediction and Motion Control for JAIST Active Robotic Walker
Authors: Ohnuma, Takanori
Lee, Geunho
Chong, Nak Young
Keywords: robotic walker
walking pattern
particle filter
walking behavior state determination
Issue Date: 2014-08
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Magazine name: 2014 RO-MAN: The 23rd IEEE International Symposium on Robot and Human Interactive Communication
Start page: 6
End page: 11
DOI: 10.1109/ROMAN.2014.6926222
Abstract: This paper presents an interactive control for our assistive robotic walker, the JAIST Active Robotic Walker (JARoW), developed for elderly people in need of walking assistance. The focus of our paper is placed on how to estimate the user's walking parameters by sensing the locations of lower limbs and to predict his or her walking patterns. For this purpose, a particle-filter-based prediction technique and a motion controller are developed to help JARoW smoothly generate the direction and velocity of its movements in a way that reflects the prediction. The proposed scheme and its implementation are described in detail, and outdoor experiments are performed to demonstrate its effectiveness and feasibility in everyday environments.
Rights: This is the author's version of the work. Copyright (C) 2014 IEEE. 2014 RO-MAN: The 23rd IEEE International Symposium on Robot and Human Interactive Communication, 2014, 6-11. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
URI: http://hdl.handle.net/10119/12345
Material Type: author
Appears in Collections:b11-1. 会議発表論文・発表資料 (Conference Papers)

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