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Real Time Implementation of Map Aided Positioning Using a Bayesian Approach (Electronics Project)

With the simple means of a digitized map and the wheel speed signals, it is possible to position a vehicle with an accuracy comparable to GPS. The positioning problem is a non-linear filtering problem and a particle filter has been applied to solve it.

Two new approaches studied are the Auxiliary Particle Filter (APF), that aims at lowerering the variance of the error, and Rao-Blackwellization that exploits the linearities in the model. The results show that these methods require problems of higher complexity to fully utilize their advantages.

Another aspect in this study has been to handle off-road driving scenarios, using dead reckoning. An off road detection mechanism has been developed and the results show that off-road driving can be detected accurately. The algorithm has been successfully implemented on a hand-held computer by quantizing the particle filter while keeping good filter performance.
Source: Linköping University
Author: Svenzén, Niklas

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One comment on “Real Time Implementation of Map Aided Positioning Using a Bayesian Approach (Electronics Project)

  1. raju jha said:

    This project is very interesting

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