Localization approaches typically rely on an already available map to identify the position of
the sensor in the environment. Such maps are usually built beforehand and often require the …

Accurate localization in indoor environments is widely regarded as a key opener for various
location-based services. Despite tremendous advancements in the development of …

This paper studies indoor localisation problem by using low-cost and pervasive sensors.
Most of existing indoor localisation algorithms rely on camera, laser scanner, floor plan or …

High-precision indoor localization is growing extremely quickly, especially for multi-floor
scenarios. The data on existing indoor positioning schemes, mainly, come from wireless …

The sheer volume of data generated by depth cameras provides a challenge to process in
real time, in particular when used for indoor mobile robot localization and navigation. We …

Indoor positioning often requires detecting and recognizing ad-hoc landmarks or anchor
points with known coordinates and/or a given orientation within a given reference frame …

In past years, there has been significant progress in the field of indoor robot localization. To
precisely recover the position, the robots usually relies on multiple on-board sensors …

Most existing approaches to indoor localization focus on using either cameras or laser
scanners as the primary sensor for pose estimation. In scan matching based localization …

We present here the Fast Sampling Plane Filtering (FSPF) algorithm, which reduces the
volume of the 3D point cloud by sampling points from the depth image, and classifying local …

We present an indoor localisation system that integrates different sensor modalities, namely
Wi-Fi, barometer, iBeacons, step-detection and turn-detection for localisation of pedestrians …