3,385 research outputs found

    State of the art review on walking support system for visually impaired people

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    The technology for terrain detection and walking support system for blind people has rapidly been improved the last couple of decades but to assist visually impaired people may have started long ago. Currently, a variety of portable or wearable navigation system is available in the market to help the blind for navigating their way in his local or remote area. The focused category in this work can be subgroups as electronic travel aids (ETAs), electronic orientation aids (EOAs) and position locator devices (PLDs). However, we will focus mainly on electronic travel aids (ETAs). This paper presents a comparative survey among the various portable or wearable walking support systems as well as informative description (a subcategory of ETAs or early stages of ETAs) with its working principal advantages and disadvantages so that the researchers can easily get the current stage of assisting blind technology along with the requirement for optimising the design of walking support system for its users

    Web-based indoor positioning system using QR-codes as markers

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    Location tracking has been quite an important tool in our daily life. The outdoor location tracking can easily be supported by GPS. However, the technology of tracking smart device users indoor position is not at the same maturity level as outdoor tracking. AR technology could enable the tracking on users indoor location by scanning the AR marker with their smart devices. However, due to several limitations (capacity, error tolerance, etc.) AR markers are not widely adopted. Therefore, not serving as a good candidate to be a tracking marker. This paper carries out a research question whether QR code can replace the AR marker as the tracking marker to detect smart devices’ user indoor position. The paper has discussed the research question by researching the background of the QR code and AR technology. According to the research, QR code should be a suitable choice to implement as a tracking marker. Comparing to the AR marker, QR code has a better capacity, higher error tolerance, and widely adopted. Moreover, a web application has also been implemented as an experiment to support the research question. It utilized QR code as a tracking marker for AR technology which built a 3D model on the QR code. Hence, the position of the user can be estimated from the 3D model. This paper discusses the experiment result by comparing a pre-fixed target user’s position and real experiment position with three different QR code samples. The limitation of the experiment and improvement ideas have also been discussed in this paper. According to the experiment, the research question has being answered that a combination of QR code and AR technology could deliver a satisfying indoor location result in a smart device user

    Comparative analysis of computer-vision and BLE technology based indoor navigation systems for people with visual impairments

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    Background: Considerable number of indoor navigation systems has been proposed to augment people with visual impairments (VI) about their surroundings. These systems leverage several technologies, such as computer-vision, Bluetooth low energy (BLE), and other techniques to estimate the position of a user in indoor areas. Computer-vision based systems use several techniques including matching pictures, classifying captured images, recognizing visual objects or visual markers. BLE based system utilizes BLE beacons attached in the indoor areas as the source of the radio frequency signal to localize the position of the user. Methods: In this paper, we examine the performance and usability of two computer-vision based systems and BLE-based system. The first system is computer-vision based system, called CamNav that uses a trained deep learning model to recognize locations, and the second system, called QRNav, that utilizes visual markers (QR codes) to determine locations. A field test with 10 blindfolded users has been conducted while using the three navigation systems. Results: The obtained results from navigation experiment and feedback from blindfolded users show that QRNav and CamNav system is more efficient than BLE based system in terms of accuracy and usability. The error occurred in BLE based application is more than 30% compared to computer vision based systems including CamNav and QRNav. Conclusions: The developed navigation systems are able to provide reliable assistance for the participants during real time experiments. Some of the participants took minimal external assistance while moving through the junctions in the corridor areas. Computer vision technology demonstrated its superiority over BLE technology in assistive systems for people with visual impairments. - 2019 The Author(s).Scopu

    IONet: Learning to Cure the Curse of Drift in Inertial Odometry

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    Inertial sensors play a pivotal role in indoor localization, which in turn lays the foundation for pervasive personal applications. However, low-cost inertial sensors, as commonly found in smartphones, are plagued by bias and noise, which leads to unbounded growth in error when accelerations are double integrated to obtain displacement. Small errors in state estimation propagate to make odometry virtually unusable in a matter of seconds. We propose to break the cycle of continuous integration, and instead segment inertial data into independent windows. The challenge becomes estimating the latent states of each window, such as velocity and orientation, as these are not directly observable from sensor data. We demonstrate how to formulate this as an optimization problem, and show how deep recurrent neural networks can yield highly accurate trajectories, outperforming state-of-the-art shallow techniques, on a wide range of tests and attachments. In particular, we demonstrate that IONet can generalize to estimate odometry for non-periodic motion, such as a shopping trolley or baby-stroller, an extremely challenging task for existing techniques.Comment: To appear in AAAI18 (Oral

    Dynamic Obstacle Detection

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    The Smart Cane was designed as an enhancement for the traditional white cane used by the visually impaired for navigation. While the traditional white cane is effective in navigating ground level obstacles such as pits, stairs and so on and so forth, it is significantly inefficient in detecting obstacles above knee height, such as trucks, cars and so on. To solve this shortcoming, a group of students under their post-doctoral guide in Indian Institute of Technology, Delhi created Smart Cane, an add-on for the existing white cane that used ultrasonic ranging to determine the nearest threats to the user and set up an advance warning system for the same. It uses a tactile feedback system to warn the user of approaching obstacles with an effective range of 0.5 – 1.8 / 3 m. It has two modes: short range and long range which correspond to the variable maximum ranges, respectively. It is also significantly cheaper than the alternative walking aid enhancements offered by a variety of companies and boasts of a long battery life (Preliminary tests claim that the aid can last for up to a week with only a single charge of three to four hours). However, the Smart Cane has its own drawback in the sense that it is unable to warn its user of moving vehicles, such as cars, bikes and the like which possess a significant threat to the visually impaired given that they are unable to detect them and are hence at constant danger while navigating crowded roads. The goal of this project is to supplant the existing Smart Cane with an additional IR sensor that makes it capable of detecting moving vehicles coming towards the user and warn the user if it is a threat to the wellbeing of the user. It functions in the “toward” mode, i.e. it only detects the objects coming towards the user and has an effective range of 250 m in optimum conditions. It uses the existing tactile feedback system to warn the user of approaching dangers. It relies on battery slightly more intensively than the ultrasonic sensor, but the usage can be optimized to minimize the battery drain

    Service-oriented Context-aware Framework

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    Location- and context-aware services are emerging technologies in mobile and desktop environments, however, most of them are difficult to use and do not seem to be beneficial enough. Our research focuses on designing and creating a service-oriented framework that helps location- and context-aware, client-service type application development and use. Location information is combined with other contexts such as the users' history, preferences and disabilities. The framework also handles the spatial model of the environment (e.g. map of a room or a building) as a context. The framework is built on a semantic backend where the ontologies are represented using the OWL description language. The use of ontologies enables the framework to run inference tasks and to easily adapt to new context types. The framework contains a compatibility layer for positioning devices, which hides the technical differences of positioning technologies and enables the combination of location data of various sources

    SLAM for Visually Impaired People: A Survey

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    In recent decades, several assistive technologies for visually impaired and blind (VIB) people have been developed to improve their ability to navigate independently and safely. At the same time, simultaneous localization and mapping (SLAM) techniques have become sufficiently robust and efficient to be adopted in the development of assistive technologies. In this paper, we first report the results of an anonymous survey conducted with VIB people to understand their experience and needs; we focus on digital assistive technologies that help them with indoor and outdoor navigation. Then, we present a literature review of assistive technologies based on SLAM. We discuss proposed approaches and indicate their pros and cons. We conclude by presenting future opportunities and challenges in this domain.Comment: 26 pages, 5 tables, 3 figure

    Realidade aumentada para produção assistida em ambiente industrial

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    Smart factories are becoming more and more common and Augmented Reality (AR) is a pillar of the transition to Industry 4.0 and smart manufacturing. AR can improve many industrial processes such as training, maintenance, assembly, quality control, remote collaboration and others. AR has the potential to revolutionize the way information is accessed, used and exchanged, extending user’s perception and improving their performance. This work proposes a Pervasive AR tool, created in collaboration with industrial partners, to support the training of operators on industrial shop floors while performing production operations. A Human-Centered Design (HCD) methodology was used to identify operators’ difficulties, challenges, and define requirements. After initial meetings with stakeholders, an AR prototype was designed and developed to allow the configuration and visualization of AR content on the shop floor. Several meetings and user studies were conducted to evaluate the developed tools and improve their usability and features. Comparisons between the proposed Head Mounted Display (HMD) solution, the method currently being used in the shopfloor and alternative AR solutions (mobile based) were conducted. The results of user studies suggest that the proposed AR system can significantly improve the performance (up to 70% when compared with the method currently used in the shop floor) of novice operators.Fábricas inteligentes estão a tornar-se cada vez mais comuns e a Realidade Aumentada (Augmented Reality) é essencial para a transição para a Indústria 4.0 e para a produção inteligente. A AR pode ser usada para melhorar muitos processos industriais, tais como treino, assistência, montagem, controlo de qualidade, colaboração remota, entre outros. A AR tem potencial para revolucionar a maneira como a informação é acedida, usada e partilhada, expandindo a perceção do utilizador e melhorando a sua performance. Este trabalho propõe uma ferramenta de AR Pervasiva, criada em colaboração com parceiros da indústria, para ajudar no treino de operadores de chão de fábrica em tarefas de produção fabril. Para identificar as dificuldades, desafios e definir requisitos, foi seguida uma metodologia de Desenho Centrada no Utilizador (HCD). Depois de vários encontros com o público-alvo, um protótipo de AR foi desenhado e desenvolvido para permitir a configuração e visualização de conteúdo em AR na linha de montagem de uma fábrica. Diversas reuniões e testes com utilizadores foram realizados de modo a avaliar as ferramentas desenvolvidas e melhorar a usabilidade e as suas funcionalidades. Foram também realizadas comparações entre a solução de AR proposta, o método atualmente utilizado na linha de produção e uma solução alternativa de AR para dispositivos móveis. Os resultados dos testes de utilizador realizados sugerem que a solução proposta pode melhorar substancialmente a eficiência (até 70% quando comparado com método atualmente utilizado na linha de produção) de novos operadores.Mestrado em Engenharia de Computadores e Telemátic
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