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      A Systematic Review of Urban Navigation Systems for Visually Impaired People

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          Abstract

          Blind and Visually impaired people (BVIP) face a range of practical difficulties when undertaking outdoor journeys as pedestrians. Over the past decade, a variety of assistive devices have been researched and developed to help BVIP navigate more safely and independently. In addition, research in overlapping domains are addressing the problem of automatic environment interpretation using computer vision and machine learning, particularly deep learning, approaches. Our aim in this article is to present a comprehensive review of research directly in, or relevant to, assistive outdoor navigation for BVIP. We breakdown the navigation area into a series of navigation phases and tasks. We then use this structure for our systematic review of research, analysing articles, methods, datasets and current limitations by task. We also provide an overview of commercial and non-commercial navigation applications targeted at BVIP. Our review contributes to the body of knowledge by providing a comprehensive, structured analysis of work in the domain, including the state of the art, and guidance on future directions. It will support both researchers and other stakeholders in the domain to establish an informed view of research progress.

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          1 year, 1000 km: The Oxford RobotCar dataset

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            Microsoft coo: common objects in context

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              Wearable Obstacle Avoidance Electronic Travel Aids for Blind: A Survey

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                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                Sensors (Basel)
                Sensors (Basel)
                sensors
                Sensors (Basel, Switzerland)
                MDPI
                1424-8220
                29 April 2021
                May 2021
                : 21
                : 9
                : 3103
                Affiliations
                [1 ]School of Computer Science, Technological University Dublin, D07EWV4 Dublin, Ireland; fatma.e.eltaher@ 123456mytudublin.ie (F.E.-z.E.-t.); ayman.farahat@ 123456tudublin.ie (A.T.); jane.courtney@ 123456tudublin.ie (J.C.)
                [2 ]Faculty of Computers and Artificial Intelligence, Cairo University, Cairo 12613, Egypt
                Author notes
                Author information
                https://orcid.org/0000-0002-9175-7855
                Article
                sensors-21-03103
                10.3390/s21093103
                8125253
                33946857
                e5a37fa1-bc09-4aa3-a610-f63e47241b0f
                © 2021 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( https://creativecommons.org/licenses/by/4.0/).

                History
                : 31 March 2021
                : 25 April 2021
                Categories
                Review

                Biomedical engineering
                assistive systems,navigation systems,visually impaired people,smart cities,planning journeys,independent children navigation,obstacle avoidance,autonomous driving,robot navigation

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