Abstract Development of Simultaneous Localization and Mapping (SLAM) systems in the era
of autonomous navigation and the growing demand for autonomous robots have put into …

Vehicle localization is the primary information needed for advanced tasks like navigation.
This information is usually provided by the use of Global Positioning System (GPS) …

In Global Navigation Satellite System (GNSS) positioning, urban environments represent an
issue particularly because of multipath and nonline-of-sight effects. The latter effects induce …

In urban areas or space-constrained environments with obstacles, vehicle localization using
Global Navigation Satellite System (GNSS) data is hindered by Non-Line Of Sight (NLOS) …

Localization is a part of many automotive applications where safety is of crucial importance.
We think that the best way to guarantee the safety in these applications is to guarantee the …

Probabilistic techniques (such as Extended Kalman Filter and Particle Filter) have long been
used to solve robotic localization and mapping problem. Despite their good performance in …

Simultaneous localization and mapping (SLAM) is widely used by autonomous robots
operating in unknown environments. Research community has developed numerous SLAM …

In future smart environments, mobile applications will find a dynamically varying number of
networked sensors that offer their measurement data. This additional information supports …

Mobile robot localization consists in estimation of robot pose by using real-time
measurements. The Internet of Things (IoT) adds a new dimension to this process by …

Mobile robot localization consists in estimating the robot coordinates using real-time
measurements. In ambient environment context, data can come both from the robot on …