Understanding the new SQL: a complete guide
Understanding the new SQL: a complete guide
Learning metric-topological maps for indoor mobile robot navigation
Artificial Intelligence
The spatial semantic hierarchy
Artificial Intelligence
Robust Monte Carlo localization for mobile robots
Artificial Intelligence
GIS for the Urban Environment
Mapping Global Cities: GIS Methods in Urban Analysis
Mapping Global Cities: GIS Methods in Urban Analysis
Advances in Mobile Mapping Technology: ISPRS Series, volume 4
Advances in Mobile Mapping Technology: ISPRS Series, volume 4
A tutorial on particle filters for online nonlinear/non-GaussianBayesian tracking
IEEE Transactions on Signal Processing
Map-based navigation in mobile robots
Cognitive Systems Research
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In order to solve most of the existing mobile robotics applications, the robot needs some information about its spatial environment encoded in what it has been commonly called a map. The knowledge contained in such a map, whatever approach is used to obtain it, will mainly be used by the robot to gain the ability to navigate in a given environment. We are describing in this paper, a method that allows a robot or team of robots to navigate in large urban areas for which an existing map in a standard human understandable fashion is available. As detailed maps of most urban areas already exist, it will be assumed that a map of the zone where the robot is supposed to work is given, which has not been constructed using the robot's own sensors. We propose in this paper, the use of an existing Geographical Information System based map of an urban zone so that a robot or a team of robots can connect to this map and use it for navigation purposes. Details of the implemented system architecture as well as a position tracking experiment in a real outdoor environment, a University Campus, are provided.