A University Indoors Audio-Tactile Mobility Aid for Individuals with Blindness

Papadopoulos, Konstantinos; Barouti, Marialena; Charitakis, Konstantinos

doi:10.1007/978-3-319-08599-9_17

Cited by 17 publications

(5 citation statements)

References 16 publications

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“…Recently, there is a growing interest in technologies for automating indoor tactile map making. For example, the Audio-Tactile navigation system by Papadopoulos et al generates audio-tactile maps from digital map files containing specific spatial information of a building [18]. Hybrid methods for the automatic generation of 3D indoor maps from AutoCAD architectural floor plans were proposed in [22,1].…”

Section: Related Workmentioning

confidence: 99%

A Multi-scale Embossed Map Authoring Tool for Indoor Environments

Trinh

Manduchi

2020

Lecture Notes in Computer Science

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We introduce a multi-scale embossed map authoring tool (M-EMAT) that produces tactile maps of indoor environments from the building's structural layout and its 3D-scanned interiors on demand. Our tool renders indoor tactile maps at different spatial scales, representing a building's structure, a zoomed-in of a specific area, or an interior of a room. M-EMAT is very easy to use and produces accurate results even in the case of complex building layouts.

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Section: Related Workmentioning

confidence: 99%

A Multi-scale Embossed Map Authoring Tool for Indoor Environments

Trinh

Manduchi

2020

Lecture Notes in Computer Science

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“…Since the information of a place is readily provided on the audio-tactile maps, the learning process is independent and Indonesian J Elec Eng & Comp Sci ISSN: 2502-4752  the user can explore the maps repeatedly which would give them enough time to form the cognitive maps and familiar with the place at the preparation stage before they initiate their wayfinding in reality [24]. The use of audio-tactile maps would help to alleviate the problems associated with the teaching process [25] since the learning of a place can be independent and the mobility instructor can focus on the blind students who needs his or her attention throughout the map learning process. Figure 5.…”

Section: The Use Of Technology To Address the Identified Problemsmentioning

confidence: 99%

Wayfinding learning techniques and its challenges: a case study at malaysian association for the blind (MAB)

Hamid

Adnan

Razak

2019

IJEECS

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<span>Navigating safely in the real environment especially in the outdoor setting requires a blind person to be equipped with the spatial knowledge and possess the skills in mobility and orientation. The aims of this study are to investigate the existing wayfinding learning techniques taught to blind people and to identify the challenges during the teaching and learning processes. A two days of observation during a mobility practical session was conducted at Malaysian Association for the Blind (MAB). The first objective was to explore the current techniques used by mobility instructor to teach visually impaired students for a wayfinding and second, to identify the challenges faced by the mobility instructor and the visually impaired students in the teaching and learning processes of wayfinding. The study discovered that the major problem faced by the mobility instructor was with the lack of teaching aids to describe a new environment to visually impaired students. This leads to the lack of time that caused the visually impaired students perceived insufficient information which was hard for them to construct the intended cognitive maps. From the findings, this paper concludes by discussing the recommendations primarily on the use of technology in addressing the problems identified in this study.</span>

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“…However, not all VI individuals can read and understand the tactile maps [5]. Apart from that, the tactile maps have limitations, including static information about the changing surroundings, and the difficulty of a VI person to position themselves [6]. A white cane is a luminous physical aid that allows a VI person to scan their surrounding for obstacles.…”

Section: Introductionmentioning

confidence: 99%

Deep Learning-Based Positioning of Visually Impaired People in Indoor Environments

Mahida

Shahrestani

Cheung

2020

Sensors

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Wayfinding and navigation can present substantial challenges to visually impaired (VI) people. Some of the significant aspects of these challenges arise from the difficulty of knowing the location of a moving person with enough accuracy. Positioning and localization in indoor environments require unique solutions. Furthermore, positioning is one of the critical aspects of any navigation system that can assist a VI person with their independent movement. The other essential features of a typical indoor navigation system include pathfinding, obstacle avoidance, and capabilities for user interaction. This work focuses on the positioning of a VI person with enough precision for their use in indoor navigation. We aim to achieve this by utilizing only the capabilities of a typical smartphone. More specifically, our proposed approach is based on the use of the accelerometer, gyroscope, and magnetometer of a smartphone. We consider the indoor environment to be divided into microcells, with the vertex of each microcell being assigned two-dimensional local coordinates. A regression-based analysis is used to train a multilayer perceptron neural network to map the inertial sensor measurements to the coordinates of the vertex of the microcell corresponding to the position of the smartphone. In order to test our proposed solution, we used IPIN2016, a publicly-available multivariate dataset that divides the indoor environment into cells tagged with the inertial sensor data of a smartphone, in order to generate the training and validating sets. Our experiments show that our proposed approach can achieve a remarkable prediction accuracy of more than 94%, with a 0.65 m positioning error.

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A University Indoors Audio-Tactile Mobility Aid for Individuals with Blindness

Cited by 17 publications

References 16 publications

A Multi-scale Embossed Map Authoring Tool for Indoor Environments

A Multi-scale Embossed Map Authoring Tool for Indoor Environments

Wayfinding learning techniques and its challenges: a case study at malaysian association for the blind (MAB)

Deep Learning-Based Positioning of Visually Impaired People in Indoor Environments

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