Mobile Robot Indoor Localization Using Artificial Neural Networks and Wireless Networks
Source: University of Bern
Accurate position information of an agent (i.e. robot, animal, or people) is a requirement to accomplish several tasks. Some sensors like GPS provide global position estimation but it is restricted to outdoor environments and has an inherent imprecision of a few meters. In indoor spaces, other sensors like lasers and cameras can be used for position estimation, but they require landmarks (or maps) in the environment and a fair amount of computation to process complex algorithms. These sensors also have a limited field of view, which makes the localization task harder. In the case of video cameras, the variation of light is also a serious issue. Nowadays Wireless Networks (WN) are widely available in indoor environments and allow efficient global localization demanding relatively low computing resources.