157 research outputs found

    Instrumentation and validation of a robotic cane for transportation and fall prevention in patients with affected mobility

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    Dissertação de mestrado integrado em Engenharia Física, (especialização em Dispositivos, Microssistemas e Nanotecnologias)O ato de andar é conhecido por ser a forma primitiva de locomoção do ser humano, sendo que este traz muitos benefícios que motivam um estilo de vida saudável e ativo. No entanto, há condições de saúde que dificultam a realização da marcha, o que por consequência pode resultar num agravamento da saúde, e adicionalmente, levar a um maior risco de quedas. Nesse sentido, o desenvolvimento de um sistema de deteção e prevenção de quedas, integrado num dispositivo auxiliar de marcha, seria essencial para reduzir estes eventos de quedas e melhorar a qualidade de vida das pessoas. Para ultrapassar estas necessidades e limitações, esta dissertação tem como objetivo validar e instrumentar uma bengala robótica, denominada Anti-fall Robotic Cane (ARCane), concebida para incorporar um sistema de deteção de quedas e um mecanismo de atuação que possibilite a prevenção de quedas, ao mesmo tempo que assiste a marcha. Para esse fim, foi realizada uma revisão do estado da arte em bengalas robóticas para adquirir um conhecimento amplo e aprofundado dos componentes, mecanismos e estratégias utilizadas, bem como os protocolos experimentais, principais resultados, limitações e desafios em dispositivos existentes. Numa primeira fase, foi estipulado o objetivo de: (i) adaptar a missão do produto; (ii) estudar as necessidades do consumidor; e (iii) atualizar as especificações alvo da ARCane, continuação do trabalho de equipa, para obter um produto com design e engenharia compatível com o mercado. Foi depois estabelecida a arquitetura de hardware e discutidos os componentes a ser instrumentados na ARCane. Em seguida foram realizados testes de interoperabilidade a fim de validar o funcionamento singular e coletivo dos componentes. Relativamente ao controlo de movimento, foi desenvolvido um sistema inovador, de baixo custo e intuitivo, capaz de detetar a intenção do movimento e de reconhecer as fases da marcha do utilizador. Esta implementação foi validada com seis voluntários saudáveis que realizaram testes de marcha com a ARCane para testar sua operabilidade num ambiente de contexto real. Obteve-se uma precisão de 97% e de 90% em relação à deteção da intenção de movimento e ao reconhecimento da fase da marcha do utilizador. Por fim, foi projetado um método de deteção de quedas e mecanismo de prevenção de quedas para futura implementação na ARCane. Foi ainda proposta uma melhoria do método de deteção de quedas, de modo a superar as limitações associadas, bem como a proposta de dispositivos de deteção a serem implementados na ARCane para obter um sistema completo de deteção de quedas.The act of walking is known to be the primitive form of the human being, and it brings many benefits that motivate a healthy and active lifestyle. However, there are health conditions that make walking difficult, which, consequently, can result in worse health and, in addition, lead to a greater risk of falls. Thus, the development of a fall detection and prevention system integrated with a walking aid would be essential to reduce these fall events and improve people quality of life. To overcome these needs and limitations, this dissertation aims to validate and instrument a cane-type robot, called Anti-fall Robotic Cane (ARCane), designed to incorporate a fall detection system and an actuation mechanism that allow the prevention of falls, while assisting the gait. Therefore, a State-of-the-Art review concerning robotic canes was carried out to acquire a broad and in-depth knowledge of the used components, mechanisms and strategies, as well as the experimental protocols, main results, limitations and challenges on existing devices. On a first stage, it was set an objective to (i) enhance the product's mission statement; (ii) study the consumer needs; and (iii) update the target specifications of the ARCane, extending teamwork, to obtain a product with a market-compatible design and engineering that meets the needs and desires of the ARCane users. It was then established the hardware architecture of the ARCane and discussed the electronic components that will instrument the control, sensory, actuator and power units, being afterwards subjected to interoperability tests to validate the singular and collective functioning of cane components altogether. Regarding the motion control of robotic canes, an innovative, cost-effective and intuitive motion control system was developed, providing user movement intention recognition, and identification of the user's gait phases. This implementation was validated with six healthy volunteers who carried out gait trials with the ARCane, in order to test its operability in a real context environment. An accuracy of 97% was achieved for user motion intention recognition and 90% for user gait phase recognition, using the proposed motion control system. Finally, it was idealized a fall detection method and fall prevention mechanism for a future implementation in the ARCane, based on methods applied to robotic canes in the literature. It was also proposed an improvement of the fall detection method in order to overcome its associated limitations, as well as detection devices to be implemented into the ARCane to achieve a complete fall detection system

    Wearable sensors for human–robot walking together

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    Thanks to recent technological improvements that enable novel applications beyond the industrial context, there is growing interest in the use of robots in everyday life situations. To improve the acceptability of personal service robots, they should seamlessly interact with the users, understand their social signals and cues and respond appropriately. In this context, a few proposals were presented to make robots and humans navigate together naturally without explicit user control, but no final solution has been achieved yet. To make an advance toward this end, this paper proposes the use of wearable Inertial Measurement Units to improve the interaction between human and robot while walking together without physical links and with no restriction on the relative position between the human and the robot. We built a prototype system, experimented with 19 human participants in two different tasks, to provide real-time evaluation of gait parameters for a mobile robot moving together with a human, and studied the feasibility and the perceived usability by the participants. The results show the feasibility of the system, which obtained positive feedback from the users, giving valuable information for the development of a natural interaction system where the robot perceives human movements by means of wearable sensors

    Human-Robot Interaction Strategies for Walker-Assisted Locomotion

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    Neurological and age-related diseases affect human mobility at different levels causing partial or total loss of such faculty. There is a significant need to improve safe and efficient ambulation of patients with gait impairments. In this context, walkers present important benefits for human mobility, improving balance and reducing the load on their lower limbs. Most importantly, walkers induce the use of patients residual mobility capacities in different environments. In the field of robotic technologies for gait assistance, a new category of walkers has emerged, integrating robotic technology, electronics and mechanics. Such devices are known as robotic walkers, intelligent walkers or smart walkers One of the specific and important common aspects to the field of assistive technologies and rehabilitation robotics is the intrinsic interaction between the human and the robot. In this thesis, the concept of Human-Robot Interaction (HRI) for human locomotion assistance is explored. This interaction is composed of two interdependent components. On the one hand, the key role of a robot in a Physical HRI (pHRI) is the generation of supplementary forces to empower the human locomotion. This involves a net flux of power between both actors. On the other hand, one of the crucial roles of a Cognitive HRI (cHRI) is to make the human aware of the possibilities of the robot while allowing him to maintain control of the robot at all times. This doctoral thesis presents a new multimodal human-robot interface for testing and validating control strategies applied to a robotic walkers for assisting human mobility and gait rehabilitation. This interface extracts navigation intentions from a novel sensor fusion method that combines: (i) a Laser Range Finder (LRF) sensor to estimate the users legs kinematics, (ii) wearable Inertial Measurement Unit (IMU) sensors to capture the human and robot orientations and (iii) force sensors measure the physical interaction between the humans upper limbs and the robotic walker. Two close control loops were developed to naturally adapt the walker position and to perform body weight support strategies. First, a force interaction controller generates velocity outputs to the walker based on the upper-limbs physical interaction. Second, a inverse kinematic controller keeps the walker within a desired position to the human improving such interaction. The proposed control strategies are suitable for natural human-robot interaction as shown during the experimental validation. Moreover, methods for sensor fusion to estimate the control inputs were presented and validated. In the experimental studies, the parameters estimation was precise and unbiased. It also showed repeatability when speed changes and continuous turns were performed

    Improving domiciliary robotic services by integrating the ASTRO Robot in an AmI Infrastructure

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    This work describes the ECHORD Experiment ASTROMOBILE, a project aimed to design, develop and test a system for favourable independent living, improved quality of life and efficiency of care for senior citizens in domestic environments. The system, composed of a mobile robotic platform (called ASTRO) and an Ambient Intelligent Infrastructure that actively cooperated between them and with the end-user, was designed and implemented with a user-centred design approach, involving different stakeholders. The system was designed to deliver services to users, like drug delivery, stand support, reminding, info-entertainment. The design took advantages of the integration of robotic platforms with smart environments, to provide to users higher quality and localization based services. Senior end-users were involved in the experimentation of the system in the DomoCasa Living Lab and feedbacks were gathered for the technology assessment. Particularly, this paper demonstrates the general feasibility of the ASTROMOBILE system and thanks to users feedbacks its acceptability and usability

    Hardware for recognition of human activities: a review of smart home and AAL related technologies

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    Activity recognition (AR) from an applied perspective of ambient assisted living (AAL) and smart homes (SH) has become a subject of great interest. Promising a better quality of life, AR applied in contexts such as health, security, and energy consumption can lead to solutions capable of reaching even the people most in need. This study was strongly motivated because levels of development, deployment, and technology of AR solutions transferred to society and industry are based on software development, but also depend on the hardware devices used. The current paper identifies contributions to hardware uses for activity recognition through a scientific literature review in the Web of Science (WoS) database. This work found four dominant groups of technologies used for AR in SH and AAL—smartphones, wearables, video, and electronic components—and two emerging technologies: Wi-Fi and assistive robots. Many of these technologies overlap across many research works. Through bibliometric networks analysis, the present review identified some gaps and new potential combinations of technologies for advances in this emerging worldwide field and their uses. The review also relates the use of these six technologies in health conditions, health care, emotion recognition, occupancy, mobility, posture recognition, localization, fall detection, and generic activity recognition applications. The above can serve as a road map that allows readers to execute approachable projects and deploy applications in different socioeconomic contexts, and the possibility to establish networks with the community involved in this topic. This analysis shows that the research field in activity recognition accepts that specific goals cannot be achieved using one single hardware technology, but can be using joint solutions, this paper shows how such technology works in this regard

    Secure indoor navigation and operation of mobile robots

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    In future work environments, robots will navigate and work side by side to humans. This raises big challenges related to the safety of these robots. In this Dissertation, three tasks have been realized: 1) implementing a localization and navigation system based on StarGazer sensor and Kalman filter; 2) realizing a human-robot interaction system using Kinect sensor and BPNN and SVM models to define the gestures and 3) a new collision avoidance system is realized. The system works on generating the collision-free paths based on the interaction between the human and the robot.In zukünftigen Arbeitsumgebungen werden Roboter navigieren nebeneinander an Menschen. Das wirft Herausforderungen im Zusammenhang mit der Sicherheit dieser Roboter auf. In dieser Dissertation drei Aufgaben realisiert: 1. Implementierung eines Lokalisierungs und Navigationssystem basierend auf Kalman Filter: 2. Realisierung eines Mensch-Roboter-Interaktionssystem mit Kinect und AI zur Definition der Gesten und 3. ein neues Kollisionsvermeidungssystem wird realisiert. Das System arbeitet an der Erzeugung der kollisionsfreien Pfade, die auf der Wechselwirkung zwischen dem Menschen und dem Roboter basieren

    Developing a person guidance module for hospital robots

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    This dissertation describes the design and implementation of the Person Guidance Module (PGM) that enables the IWARD (Intelligent Robot Swarm for attendance, Recognition, Cleaning and delivery) base robot to offer route guidance service to the patients or visitors inside the hospital arena. One of the common problems encountered in huge hospital buildings today is foreigners not being able to find their way around in the hospital. Although there are a variety of guide robots currently existing on the market and offering a wide range of guidance and related activities, they do not fit into the modular concept of the IWARD project. The PGM features a robust and foolproof non-hierarchical sensor fusion approach of an active RFID, stereovision and cricket mote sensor for guiding a patient to the X-ray room, or a visitor to a patient’s ward in every possible scenario in a complex, dynamic and crowded hospital environment. Moreover, the speed of the robot can be adjusted automatically according to the pace of the follower for physical comfort using this system. Furthermore, the module performs these tasks in any unconstructed environment solely from a robot’s onboard perceptual resources in order to limit the hardware installation costs and therefore the indoor setting support. Similar comprehensive solution in one single platform has remained elusive in existing literature. The finished module can be connected to any IWARD base robot using quick-change mechanical connections and standard electrical connections. The PGM module box is equipped with a Gumstix embedded computer for all module computing which is powered up automatically once the module box is inserted into the robot. In line with the general software architecture of the IWARD project, all software modules are developed as Orca2 components and cross-complied for Gumstix’s XScale processor. To support standardized communication between different software components, Internet Communications Engine (Ice) has been used as middleware. Additionally, plug-and-play capabilities have been developed and incorporated so that swarm system is aware at all times of which robot is equipped with PGM. Finally, in several field trials in hospital environments, the person guidance module has shown its suitability for a challenging real-world application as well as the necessary user acceptance
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