A Low-cost Inertial Rail Track Positioning Technology Based on Distributed Optical System Assistance

Foot-mounted Indoor Pedestrian Positioning System Based on Low-Cost Inertial Senors

In this paper, we present an indoor positioning system using foot-mounted low cost Micro-Electro-Mechanical System (MEMS) sensors to derive the position and attitude of the wearer and plot the trajectory on the smartphone in realtime. The pedestrian’s motion information is collected by accelerometers and gyroscopes to achieve Pedestrian DeadReckoning (PDR) which is used to estimate the pedestri...

TESTING goGPS LOW-COST RTK POSITIONING WITH A WEB-BASED TRACK LOG MANAGEMENT SYSTEM

Location-based online collaborative platforms are proving to be an effective and widely adopted solution for geospatial data collection, update and sharing. Popular collaborative projects like OpenStreetMap, Wikimapia and other services that collect and publish user-generated geographic contents have been fostered by the increasing availability of location-aware palmtop devices. These instrumen...

Low Cost Indoor Positioning System

This report describes a low cost indoor position sensing system utilising a combination of radio frequency and ultrasonics. Using a single rf transmitter and four ceiling mounted ultrasonic transmitters it provides coverage in a typical room in an area greater than 8m by 8m. As well as finding position within a room, it uses data encoded into the rf signal to determine the relevant web server f...

The Rail Technology Unit An Intelligent Track Monitoring System

Low-cost Autonomous Navigation System Based on Optical Flow Classification

This work presents a low-cost robot, controlled by a Raspberry Pi, whose navigation system is based on vision. The strategy used consisted of identifying obstacles via optical flow pattern recognition. Its estimation was done using the Lucas-Kanade algorithm, which can be executed by the Raspberry Pi without harming its performance. Finally, an SVM-based classifier was used to identify patterns...