Smartphone-based localization for blind navigation in building-scale indoor environments

Abstract

Continuous, accurate, and real-time smartphone-based localization is a promising technology for supporting independent mobility of people with visual impairments. However, despite extensive research on indoor localization techniques, localization technologies are still not ready for deployment in large and complex environments such as shopping malls and hospitals, where navigation assistance is needed most. We identify six key challenges for accurate smartphone localization related to the large-scale nature of the navigation environments and the user's mobility. To address these challenges, we present a series of techniques that enhance a probabilistic localization algorithm. The algorithm utilizes mobile device inertial sensors and Received Signal Strength (RSS) from Bluetooth Low Energy (BLE) beacons. We evaluate the proposed system in a 21,000 m 2 shopping mall that includes three multi-story buildings and a large open underground passageway. Experiments conducted in this environment demonstrate the effectiveness of the proposed technologies to improve localization accuracy. Field experiments with visually impaired participants confirm the practical performance of the proposed system in realistic use cases.

Cost-Effective Wearable Indoor Localization and Motion Analysis via the Integration of UWB and IMU

“…Sasiadek et al [49] presented a sensor method based on a Kalman filter, which was applied to GPS/INS integration, and the universality of the method under different experimental conditions was discussed and verified. Murata et al [50] presented a series of techniques that enhance a probabilistic localization algorithm, which utilizes mobile device inertial sensors and RSS from Bluetooth low energy (BLE) beacons. Experimental studies demonstrated the effectiveness of the proposed technologies to improve the localization accuracy from 3.0 m to 1.5 m. Jiang et al [51] proposed a robot-assisted human indoor localization scheme utilizing acoustic ranging between a self-localized mobile robot and smartphones, and achieved an estimation accuracy of 0.43-1.12 m. Zhang et al [52] integrated WiFi fingerprinting with IMU location estimation and achieved a localization error of 5.7 m over 5-10 min of indoor walking.…”

A Generic Approach toward Indoor Navigation and Pathfinding with Robust Marker Tracking

“…Smartphone-based applications are common in indoor navigation, as it allows free user mobility. Murata et al [6] identified six challenges mainly concerned with user mobility, and localization in large scale indoor environments (see Section 1). They proposed a new system to handle these issues.…”

“…Typically, a user navigating in an indoor environment needs two types of information including his/her own position and a path toward his/her specific destination [5]. A recent study [6] identified the following challenges usually considered for navigation and localization of user in large scale environments. (1) Accuracy and continuity: The accuracy and continuity of locations are important, especially for visually impaired people.…”

“…However, incase if the internal sensors missed the steps, it may cause a noticeable localization error. (6) Delay Detection: The delay in signal is also a challenging issue in indoor navigation. The delayed data may cause to mislead a user, particularly at decision points such as corridor intersections, stairs, and entrances.…”

Accurate Self-Localization in Transit Stations: A Case Study

“…The use of BLE beacons in the outdoors, for situations with poor GPS reception, has received much less attention by the research community. In fact, whereas BLE beacons have been shown to produce acceptable localization accuracy in places characterized by networks of corridors [1], where the user's path is well constrained, they turn out to be much less effective in open spaces, where the large variance of their transmission power often results in large localization error [2].…”