Indoor Navigation System for the Visually Impaired with User-centric Graph Representation and Vision Detection Assistance

Independent navigation through unfamiliar indoor spaces is beset with barriers for the visually impaired. Hence, this issue impairs their independence, self-respect and self-reliance. In this thesis I will introduce a new indoor navigation system for the blind and visually impaired that is affordable for both the user and the building owners. Outdoor vehicle navigation technical challenges have been solved using location information provided by Global Positioning Systems (GPS) and maps using Geographical Information Systems (GIS). However, GPS and GIS information is not available for indoor environments making indoor navigation, a challenging technical problem. Moreover, the indoor navigation system needs to be developed with the blind user in mind, i.e., special care needs to be given to vision free user interface. In this project, I design and implement an indoor navigation application for the blind and visually impaired that uses RFID technology and Computer Vision for localization and a navigation map generated automatically based on environmental landmarks by simulating a user’s behavior. The focus of the indoor navigation system is no longer only on the indoor environment itself, but the way the blind users can experience it. This project will try this new idea in solving indoor navigation problems for blind and visually impaired users

Scalable and Vision Free User Interface Approaches for Indoor Navigation Systems for the Visually Impaired

This thesis introduces scalable and vision free user interface approaches for indoor navigation systems for the visually impaired. Using an Android Smartphone that runs the indoor navigation system – Percept Application with accessibility features, the blind user obtains navigation instructions generated automatically by our navigation generation algorithm to the chosen destination when touching specific landmarks tagged with Near Field Communication tags. This thesis also introduces an Orientation & Mobility Survey Tool that can help O&M Instructors survey the building and deploy such indoor navigation system. The system was deployed and tested in a large building at the University of Massachusetts at Amherst

Real-time rss-based indoor navigation for autonomous UAV flight

Navigation for the autonomous flight of Unmanned Aerial Vehicles (UAVs) in an indoor space has attracted much attention recently. One of the main goals of an indoor navigation system is developing an alternative method to obtain position information that can replace or complement the global positioning system. While much research has focused on vision-based indoor navigation systems, this paper aims to develop a Received Signal Strength (RSS)-based navigation system, which is a more cost effective alternative. Then, the position and attitude of a UAV can be computed by the fusion of RSS measurements and measurements from the onboard inertial measurement unit. In order to improve the estimation accuracy, we first consider a mathematical model of the RSS-based navigation system and formulate optimization problems to compute the parameter values which minimize the RSS measurement error. Using the optimal parameters, an autonomous flight system is developed whose estimator and controller components are designed to work well with the RSS-based navigation system. Simulations and experiments using a quadrotor demonstrate the feasibility and performance of the proposed RSS-based navigation system for UAVs operating in indoor environments

Development of Semantic Model of Multi-Level-Building Navigation Using Indoor Ontology and Dijkstra's Algorithm

Location based services (LBS) can be separated into a number of layers: technology layer, application layer, standard layer, and social-ethical layer. This paper presents an ontology development at standard layer. We developed an ontology to identify and classify indoor semantic information to guide the development of LBS applications for multi-level building navigation. This ontology proposed models of multilevel building properties as classes of building, level, zone, link, node, and coordinate. To apply this ontology, we develop an indoor navigation algorithm using the ontology classes and Dijkstra’s algorithm for shortest path in user navigation. A prototype and experiments are implemented to validate this ontology