文件列表:

AWrap.m (71, 2014-09-29)
AckermannModel.m (286, 2014-09-29)
DOIS (0, 2014-09-29)
DOIS\Sensors.csv (1076, 2014-09-29)
DOIS\gps.csv (720, 2014-09-29)
DeadReckoning.m (7851, 2014-09-29)
DrawCar.m (1787, 2014-09-29)
DrawSimpleCar.m (1814, 2014-09-29)
LICENSE (1090, 2014-09-29)
Localization.m (9140, 2014-09-29)
Measurements (0, 2014-09-29)
Measurements\Sensors.csv (341, 2014-09-29)
PlotEllipse.m (322, 2014-09-29)
QUATRO (0, 2014-09-29)
QUATRO\Sensors.csv (639, 2014-09-29)
QUATRO\gps.csv (460, 2014-09-29)
QUATRO\gpsx.csv (420, 2014-09-29)
QUATRO\transformation.csv (2704, 2014-09-29)
TRES (0, 2014-09-29)
TRES\Sensors.csv (607, 2014-09-29)
TRES\gps.csv (456, 2014-09-29)
TRES\transformation.csv (2696, 2014-09-29)
UM (0, 2014-09-29)
UM\Sensors.csv (1075, 2014-09-29)
UM\gps.csv (732, 2014-09-29)
VIO.m (8956, 2014-09-29)
ZERO (0, 2014-09-29)
ZERO\gps.csv (208, 2014-09-29)
ZERO\transformation.csv (1646, 2014-09-29)
plotgps.m (4822, 2014-09-29)
rodrigues.m (4876, 2014-09-29)
vectarrow.m (2537, 2014-09-29)
xMeasurements (0, 2014-09-29)
xMeasurements\Sensors.csv (2172, 2014-09-29)

Hybrid Localization for an indoor scale radio controlled car ======================= This work summarizes the experience working with few redundant localization sensors on a practical approach, performing an assessment of 3 different methods and its fusion using kalman filter ------ ###### File structure of the project | Name | Description | | ------------- | ----------- | | AckermannModel.py | kinematic model of vehicle based on ackerman steering mechanism.| | DrawCar.py | Creates a car based on its kinematic parameters |

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