Basic Research on Power Assist Walking Leg Using Force/Velocity Control Strategies

Chen, Feng; Yu, Yong; Ge, Yaojun; Sun, Jian

doi:10.1109/icia.2006.305812

Cited by 10 publications

(8 citation statements)

References 14 publications

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“…When people put on the robot, lower limb of people and this robot constitute a whole. Sensors of the robot will perceive the movement location of human body accurately, and the robot will control the motor installed on the hip and knee to drive the movement of lower limb after processing the information [8].…”

Section: The Design Of Mechanicalmentioning

confidence: 99%

Design of Information Acquisition and Control System for the Exoskeleton Robot

Gou

Wang

et al. 2014

Journal of Electrical and Computer Engineering

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This paper puts forward an information acquisition and control system for the exoskeleton robot, which can collect movement and location information of the robot timely through a variety of sensors. The information is preprocessed by the microcontroller firstly and then transmitted to the host computer for data analysis and processing by ZigBee wireless transmission module to analyze the movement intention of human by virtue of the monitoring software on the host computer. To achieve assistance, the motor drive will be controlled by the robot through CAN bus, and the robot can effectively analyze human’s intention and monitor the operation status of the assisted robot in practical applications, finally enhancing the body's walking ability.

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Section: The Design Of Mechanicalmentioning

confidence: 99%

Design of Information Acquisition and Control System for the Exoskeleton Robot

Gou

Wang

et al. 2014

Journal of Electrical and Computer Engineering

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“…The same thing has occurred in designing the power assistive systems. Several types of power assist systems have recently been proposed [4][5][6]. We have tried to develop a wearable unit for use as a biosignal-based control system, such as the cycle ergometer for the elderly [7] and electrically assisted bicycles (EAB) [8].…”

Section: Introductionmentioning

confidence: 99%

“…There have been exoskeleton-type motion assist system [12] and ones for walking restoration [5,13,14]. Since enough power is obtained from these power assist systems, we now must focus on the design of the assist timing.…”

Section: Introductionmentioning

confidence: 99%

Feasibility study on a perceived fatigue prediction dependent power control for an electrically assisted bicycle

Kiryu

Minagawa

2013

2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

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Several types of electric motor assists have been developed, as a result, it is important to control muscular fatigue on-site in terms of health promotion and motor rehabilitation. Predicting the perceived fatigue by several biosignal-related variables with the multiple regression model and polynomial approximation, we try to propose a self control design for the electrically assisted bicycle (EAB). We also determine the meaningful muscles during pedaling by muscle synergies in relation to the motion maturity. In field experiments, prediction of ongoing perceived physical fatigue could have the potential of suitable control of EAB.

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“…In order to help elderly people straight walk on the floor, go up down stairs agilely, a first generation prototype of Power Assist Walking Legs (PAWL) was developed in our laboratory (see Fig.1) [1]. Besides helping the elderly people, this device also has many other applications, such as care-worker, nurse, heavy manual worker, fireman, even for the person with gait disorder.…”

Section: Introductionmentioning

confidence: 99%

Sensing information forecasting for Power Assist Walking Legs based on time series analysis

Sun

2009

2009 International Conference on Information and Automation

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The Power Assist Walking Legs (PAWL) is an autonomous exoskeleton robot which is designed for assisting activities of daily life. In order to improve the dynamic response of the exoskeleton robot, a novel sensing information forecasting algorithm is proposed based on the time series analysis. The algorithm is built up with the autoregressive (AR) model, the recursive least square (RLS) method and the final prediction error (FPE) criterion. The method of RLS is used to make the on-line parameters estimation, and the FPE criterion is used to select the order of AR model. Because of the real-time requirement, the forecasting algorithm is designed to be used on-line and to make predictions of force sensor's information to ensure the real-time quality of the whole system. According to requirements, the algorithm can be categorized into two types: one step forecasting method and multi-step forecasting method. Meanwhile, we make some correlative simulations and experiments, and the experiments demonstrate the sensing information forecasting algorithm can predict the value and the trend of the sensing signal, the results of simulations and experiments illustrate the validity and effectiveness of the algorithm.

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Basic Research on Power Assist Walking Leg Using Force/Velocity Control Strategies

Cited by 10 publications

References 14 publications

Design of Information Acquisition and Control System for the Exoskeleton Robot

Design of Information Acquisition and Control System for the Exoskeleton Robot

Feasibility study on a perceived fatigue prediction dependent power control for an electrically assisted bicycle

Sensing information forecasting for Power Assist Walking Legs based on time series analysis

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