Indoor localization and navigation systems for individuals with Visual Impairments (VIs) typically rely upon extensive augmentation of the physical space, significant computational resources, or heavy and expensive sensors; thus, few systems have been implemented on a large scale. This work describes a system able to guide people with VIs through indoor environments using inexpensive sensors, such as accelerometers and compasses, which are available in portable devices like smart phones. The method takes advantage of feedback from the human user, who confirms the presence of landmarks, something that users with VIs already do when navigating in a building. The system calculates the user's location in real time and uses it to provide audio instructions on how to reach the desired destination. Initial early experiments suggested that the accuracy of the localization depends on the type of directions and the availability of an appropriate transition model for the user. A critical parameter for the transition model is the user's step length. Consequently, this work also investigates different schemes for automatically computing the user's step length and reducing the dependence of the approach on the definition of an accurate transition model. In this way, the direction provision method is able to use the localization estimate and adapt to failed executions of paths by the users. Experiments are presented that evaluate the accuracy of the overall integrated system, which is executed online on a smart phone. Both people with VIs and blindfolded sighted people participated in the experiments, which included paths along multiple floors that required the use of stairs and elevators.

Whereas outdoor navigation systems typically rely upon GPS, indoor systems have to rely upon dierent techniques for localizing the user, as GPS signals cannot be received indoors. Over the past decade various indoor navigation systems have been developed. This paper provides a comprehensive overview of existing indoor navigation systems and analyzes the dierent techniques used for: (1) locating the user; (2) planning a path; (3) representing the environment; and (4) interacting with the user. Our survey identies a number of research issues that could facilitate large scale deployment of indoor navigation systems.

Indoor navigation systems for users who are visually impaired typically rely upon expensive physical augmentation of the environment or expensive sensing equipment; consequently few systems have been implemented. We present an indoor navigation system called Navatar that allows for localization and navigation by exploiting the physical characteristics of indoor environments, taking advantage of the unique sensing abilities of users with visual impairments, and minimalistic sensing achievable with low cost accelerometers available in smartphones. Particle filters are used to estimate the user's location based on the accelerometer data as well as the user confirming the presence of anticipated tactile landmarks along the provided path. Navatar has a high possibility of large-scale deployment, as it only requires an annotated virtual representation of an indoor environment. A user study with six blind users determines the accuracy of the approach, collects qualitative experiences and identifies areas for improvement.

Indoor localization and navigation systems for individuals with visual impairments (VI) typically rely upon extensive augmentation of the physical space or heavy, expensive sensors; thus, few systems have been adopted. This work describes a system able to guide people with VI through buildings using inexpensive sensors, such as accelerometers, which are available in portable devices like smart phones. The method takes advantage of feedback from the human user, who confirms the presence of landmarks. The system calculates the user's location in real time and uses it to provide audio instructions on how to reach the desired destination. Previous work suggested that the accuracy of the approach depended on the type of directions and the availability of an appropriate transition model for the user. A critical parameter for the transition model is the user's step length. The current work investigates different schemes for automatically computing the user's step length and reducing the dependency of the approach to the definition of an accurate transition model. Furthermore, the direction provision method is able to use the localization estimate and adapt to failed executions of paths by the users. Experiments are presented that evaluate the accuracy of the overall integrated system, which is executed online on a smart phone. Both people with visual impairments, as well as blindfolded sighted people, participated in the experiments. The experiments included paths along multiple floors, that required the use of stairs and elevators.