An approach for fuzzy control of elderly-assistant &amp; walking-assistant robot

Han, Huanjie; Zhang, Xiaodong; Mu, Xiaoqi

doi:10.1109/urai.2017.7992725

Cited by 12 publications

(5 citation statements)

References 12 publications

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“…Currently, several developments (including robotic solutions and mobile applications) have been proposed to provide walking assistance or motivate people to go out and do physical activities. In [82], the Elderly-assistant & Walking-assistant robot has been described which is able to determine an intention of a user and identify a walking-mode. Its purpose is to provide physical support and walking assistance for older adults to meet their needs for walking autonomy, friendliness, and security [83].…”

Section: Emotions As Part Of Aal In Mobilitymentioning

confidence: 99%

Towards Truly Affective AAL Systems

Pudāne

Petroviča

Lavendelis

et al. 2019

Lecture Notes in Computer Science

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Affective computing is a growing field of artificial intelligence. It focuses on models and strategies for detecting, obtaining, and expressing various affective states, including emotions, moods, and personality related attributes. The techniques and models developed in affective computing are applicable to various affective contexts, including Ambient Assisted Living. One of the hypotheses for the origin of emotion is that the primary purpose was to regulate social interactions. Since one of the crucial characteristics of Ambient Assisted Living systems is supporting social contact, it is unthinkable to build such systems without considering emotions. Moreover, the emotional capacity needed for Ambient Assisted Living systems exceeds simple user emotion detection and showing emotion expressions of the system. In addition, emotion generation and emotion mapping on rational thinking and behavior of a system should be considered. The chapter discusses the need and requirements for these processes in the context of various application domains of Ambient Assisted Living, i.e., healthcare, mobility, education, and social interaction.

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Section: Emotions As Part Of Aal In Mobilitymentioning

confidence: 99%

Towards Truly Affective AAL Systems

Pudāne

Petroviča

Lavendelis

et al. 2019

Lecture Notes in Computer Science

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“…FLC more closely likes the way the human brain thinks and makes decisions. In fact, FLC has been effectively used to nonanalytic systems as well as time-varying nonlinear systems [12]. Human factors, particularly the creation of fuzzy rules, have an impact on FLC.…”

Section: Introductionmentioning

confidence: 99%

Development of Powered Semi-Active Ankle-Foot Prosthetic with Fuzzy Logic-PI Controller

Ibrahim

2023

JES. Journal of Engineering Sciences

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One of the most difficult issues in the design of power ankle-foot prosthetics is to create a control system that can simulate biological ankle-foot behavior in various operating conditions. The mechanical design of a novel PSAAP is studied. The powered semi-active anklefoot prosthetic is a complex nonlinear system with high coupling. For powered ankle prostheses, a fuzzy logic-proportional-integral (FLC-PI) controller is presented. In the initial stage of control, two proportional-integral (PI) controllers are designed to regulate motor speed and current, respectively. In the next stage of control, two FLC-PI controllers are designed. The PI controller's gains are intended to be adjusted online by the fuzzy logic controller. FLC-PI controllers are used to control the designated model under these external disturbances during a typical walking gait cycle. The performance of PI controllers and FLC-PI controllers are compared during the walking gait cycle. The results reveal that a powered semi-active ankle-foot prosthetic with a fuzzy logic-PI controller method outperforms a PI controller alone.

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“…For examples, a passive walker is powered by the user-supplied forces with controlled brakes [ 8 , 9 , 10 ]. Recently, the walker powered by motors to steer the walker has attracted a lot of attention [ 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 ]. Patel et al [ 11 ] used an active walker as the experimental platform to exploit the interactions between an intelligent mobility aid and the human operator.…”

Section: Introductionmentioning

confidence: 99%

“…In the vision-based approach, a camera is installed to detect the user’s movement intension [ 10 , 13 , 15 ]. On the other hand, some pressure or force sensors are mounted on the handle to detect the user’s posture [ 25 , 29 , 30 ]. For the movements like push and pull, the detection from force sensing will be more straightforward.…”

Section: Introductionmentioning

confidence: 99%

ROS-Based Smart Walker with Fuzzy Posture Judgement and Power Assistance

Chang

Sahoo

Chen

et al. 2021

Sensors

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In recent years the increased rate of the aging population has become more serious. With aging, the elderly sometimes inevitably faces many problems which lead to slow walking, unstable or weak limbs and even fall-related injuries. So, it is very important to develop an assistive aid device. In this study, a fuzzy controller-based smart walker with a distributed robot operating system (ROS) framework is designed to assist in independent walking. The combination of Raspberry Pi and PIC microcontroller acts as the control kernel of the proposed device. In addition, the environmental information and user postures can be recognized with the integration of sensors. The sensing data include the road slope, velocity of the walker, and user’s grip forces, etc. According to the sensing data, the fuzzy controller can produce an assistive force to make the walker moving more smoothly and safely. Apart from this, a mobile application (App) is designed that allows the user’s guardian to view the current status of the smart walker as well as to track the user’s location.

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An approach for fuzzy control of elderly-assistant & walking-assistant robot

Cited by 12 publications

References 12 publications

Towards Truly Affective AAL Systems

Towards Truly Affective AAL Systems

Development of Powered Semi-Active Ankle-Foot Prosthetic with Fuzzy Logic-PI Controller

ROS-Based Smart Walker with Fuzzy Posture Judgement and Power Assistance

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