RFID-based indoor positioning of autonomous aid for disable people

Nowadays, global positioning system (GPS) is widely used in localization area because it's very capable and reliable. However, in indoor positioning, GPS capabilities are very limited since the satellite signals are typically strongly attenuated by walls and ceiling. Thus, this project introduced the concept which presents a self-localization of a mobile robot by fusing radio frequency identification (RFID) system and wireless communication using XBee module to be used in indoor environment. Two Xbee devices will be used to transfer data from the remote control unit to mobile robot. Aims of this project are to create a mobile robot that reacts to the remote control to go to the desired position as command. To meet the desired aim of this project, practical and compact design technique are emphasized in order to create a mobile robot and the remote control. Sixteen RFID cards are arranged in a fixed pattern on the floor. A unique code of each RFID card provides the position data to the mobile robot. An RFID reader act as antenna will be installed to read the card data on the below of the mobile robot. The user can make it come by easily pressing the remote control by informing the user location

Helmsman, Set a Course : Using a Compass and RFID Tags for Indoor Localisation and Navigation

Localisation and navigation are still two of the most important issues in mobile robotics. In certain indoor application scenarios RFID (radio frequency identification)-based absolute localisation has been found to be especially successful in supporting navigation. In this paper we evaluate the feasibility of an RFID and compass based approach to robot localisation and navigation for indoor environments that are dominated by corridors. We describe our system and evaluate its performance in a small, but full-scale, test environment

Indoor location based services challenges, requirements and usability of current solutions

Indoor Location Based Services (LBS), such as indoor navigation and tracking, still have to deal with both technical and non-technical challenges. For this reason, they have not yet found a prominent position in people’s everyday lives. Reliability and availability of indoor positioning technologies, the availability of up-to-date indoor maps, and privacy concerns associated with location data are some of the biggest challenges to their development. If these challenges were solved, or at least minimized, there would be more penetration into the user market. This paper studies the requirements of LBS applications, through a survey conducted by the authors, identifies the current challenges of indoor LBS, and reviews the available solutions that address the most important challenge, that of providing seamless indoor/outdoor positioning. The paper also looks at the potential of emerging solutions and the technologies that may help to handle this challenge

Sensors and Systems for Indoor Positioning

This reprint is a reprint of the articles that appeared in Sensors' (MDPI) Special Issue on “Sensors and Systems for Indoor Positioning". The published original contributions focused on systems and technologies to enable indoor applications

Overcoming barriers and increasing independence: service robots for elderly and disabled people

This paper discusses the potential for service robots to overcome barriers and increase independence of elderly and disabled people. It includes a brief overview of the existing uses of service robots by disabled and elderly people and advances in technology which will make new uses possible and provides suggestions for some of these new applications. The paper also considers the design and other conditions to be met for user acceptance. It also discusses the complementarity of assistive service robots and personal assistance and considers the types of applications and users for which service robots are and are not suitable

MULTI-SENSOR LOCALIZATION AND TRACKING IN DISASTER MANAGEMENT AND INDOOR WAYFINDING FOR VISUALLY IMPAIRED USERS

This dissertation proposes a series of multi-sensor localization and tracking algorithms particularly developed for two important application domains, which are disaster management and indoor wayfinding for blind and visually impaired (BVI) users. For disaster management, we developed two different localization algorithms, one each for Radio Frequency Identification (RFID) and Bluetooth Low Energy (BLE) technology, which enable the disaster management system to track patients in real-time. Both algorithms work in the absence of any pre-deployed infrastructure along with smartphones and wearable devices. Regarding indoor wayfinding for BVI users, we have explored several types of indoor positioning techniques including BLE-based, inertial, visual and hybrid approaches to offer accurate and reliable location and orientation in complex navigation spaces. In this dissertation, significant contributions have been made in the design and implementation of various localization and tracking algorithms under different requirements of certain applications

Low cost inertial-based localization system for a service robot

Dissertation presented at Faculty of Sciences and Technology of the New University of Lisbon to attain the Master degree in Electrical and Computer Science EngineeringThe knowledge of a robot’s location it’s fundamental for most part of service robots. The success of tasks such as mapping and planning depend on a good robot’s position knowledge. The main goal of this dissertation is to present a solution that provides a estimation of the robot’s location. This is, a tracking system that can run either inside buildings or outside them, not taking into account just structured environments. Therefore, the localization system takes into account only measurements relative. In the presented solution is used an AHRS device and digital encoders placed on wheels to make a estimation of robot’s position. It also relies on the use of Kalman Filter to integrate sensorial information and deal with estimate errors. The developed system was testes in real environments through its integration on real robot. The results revealed that is not possible to attain a good position estimation using only low-cost inertial sensors. Thus, is required the integration of more sensorial information, through absolute or relative measurements technologies, to provide a more accurate position estimation