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Real-time high dimension particle filtering
Student(en):

 Betreuer:

Kariotoglou Nikolaos, Hempel Andreas B.
Beschreibung:

Particle filtering is a well-known method of state estimation for non-linear systems. However, the accuracy of the filter and the state dimensions that it can handle are directly related to the processing power of the underlying system.

In the recent years, there has been a lot of discussion on the shift of massive simulations to parallel computing architectures. For that reason, programming of generic graphical processing units (GPUs) has become a hot topic.

In this project we attempt to merge the two facts: the underlying parallelizability of particle filtering and the promising parallel computation performance of GPUs. Recent work has proven this to be a promising path towards the implementation of real-time high dimensional particle filtering. We will be testing the developed methods in going IfA projects such as the ORCA racer, Nao Z-Knipsers Robot Team and helicopter flight control.

Nikos

Requirements:



Weitere Informationen 		Professor:

John Lygeros
Projektcharakteristik:

Typ:
Art der Arbeit: Implementation
Voraussetzungen: See description
Anzahl StudentInnen:
Status: taken
Projektstart: to be discussed
Semester: Autumn/Spring