A fast parameterized gait planning method for a lower-limb exoskeleton robot

A fast parameterized gait planning method for a lower-limb exoskeleton robot

In order to meet requirements of diverse activities of exoskeleton robot in practical application, a dynamic motion planning system is proposed using a fast parameterized gait planning method in this article. This method can plan the required gait data by adaptively adjusting very few parameters acc...

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Main Authors: Hao Ren, Wanfeng Shang, Niannian Li, Xinyu Wu
Format: Article
Language:English
Published: SAGE Publishing 2020-01-01
Series:International Journal of Advanced Robotic Systems
Online Access:https://doi.org/10.1177/1729881419893221
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spelling doaj-b1c48a63e08c46b3858badf6ca7e9b2c2020-11-25T03:52:31ZengSAGE PublishingInternational Journal of Advanced Robotic Systems1729-88142020-01-011710.1177/1729881419893221A fast parameterized gait planning method for a lower-limb exoskeleton robotHao Ren0Wanfeng Shang1Niannian Li2Xinyu Wu3 University of Chinese Academy of Sciences, Beijing, China Guangdong Provincial Key Lab of Robotics and Intelligent System, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China Otolaryngology Research Institute, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai, China Guangdong Provincial Key Lab of Robotics and Intelligent System, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, ChinaIn order to meet requirements of diverse activities of exoskeleton robot in practical application, a dynamic motion planning system is proposed using a fast parameterized gait planning method in this article. This method can plan the required gait data by adaptively adjusting very few parameters according to different application requirements. The inverted pendulum model is used to ensure the sagittal stability of the robot in the planning process. And this article specifies the end location of robot and iterates the associated joint angles by inverse kinematics. The gait trajectories generated by the proposed method are applied to the lightweight lower-limb exoskeleton robot. The results demonstrate that the trajectories of gait can be online generated smoothly and correctly, meanwhile every variable step can be satisfied as expected.https://doi.org/10.1177/1729881419893221
collection DOAJ
language English
format Article
sources DOAJ
author Hao Ren
Wanfeng Shang
Niannian Li
Xinyu Wu
spellingShingle Hao Ren
Wanfeng Shang
Niannian Li
Xinyu Wu
A fast parameterized gait planning method for a lower-limb exoskeleton robot
International Journal of Advanced Robotic Systems
author_facet Hao Ren
Wanfeng Shang
Niannian Li
Xinyu Wu
author_sort Hao Ren
title A fast parameterized gait planning method for a lower-limb exoskeleton robot
title_short A fast parameterized gait planning method for a lower-limb exoskeleton robot
title_full A fast parameterized gait planning method for a lower-limb exoskeleton robot
title_fullStr A fast parameterized gait planning method for a lower-limb exoskeleton robot
title_full_unstemmed A fast parameterized gait planning method for a lower-limb exoskeleton robot
title_sort fast parameterized gait planning method for a lower-limb exoskeleton robot
publisher SAGE Publishing
series International Journal of Advanced Robotic Systems
issn 1729-8814
publishDate 2020-01-01
description In order to meet requirements of diverse activities of exoskeleton robot in practical application, a dynamic motion planning system is proposed using a fast parameterized gait planning method in this article. This method can plan the required gait data by adaptively adjusting very few parameters according to different application requirements. The inverted pendulum model is used to ensure the sagittal stability of the robot in the planning process. And this article specifies the end location of robot and iterates the associated joint angles by inverse kinematics. The gait trajectories generated by the proposed method are applied to the lightweight lower-limb exoskeleton robot. The results demonstrate that the trajectories of gait can be online generated smoothly and correctly, meanwhile every variable step can be satisfied as expected.
url https://doi.org/10.1177/1729881419893221
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