Record a Lap Using a MATLAB Script

record, storing, data manipulation, calibration

Record a Lap

After successfully recording the lab, an essential step is to provide quality data for the AI by cleaning and filtering the data(removing noice). These can be archieved through the following.

data manipulation

• Normalization:

is the set of steps applied to raw data to make it clean and suitable for analysis or modelling. It covers tasks like handling missing values, encoding categories, removing outliers, and feature scaling.

Tabelle 5: Matlab Setup For Normalisation

#	Name	Description	Pictures
1	Standardization:	Ensuring every image treated is of the same standard	Fig. 5: Camera setup for image with calibration

• Pre-processing:

Tabelle 6: Matlab Setup for Pre-processing

#	Name	Description	Pictures
1	handling missing values:	Check for valid and delete missing steering or frames	Fig. 5: Camera setup for image with calibration
2	removing outliers:	Filter and remove unnecessary layer before training	Fig. 5: Camera setup for image with calibration

calibration

There are unusual distortions caused by the camera lens on the image; these distortions can cause noises in the input, hence reducing the AI's accuracy. Fixing these distortions can be done through calibration of the camera [1]. screenshot

Results

Tabelle 6: Calibration Output

#	Name	Description	Pictures
1	Results:	Fig. 5: Camera setup for image without calibration	Fig. 5: Camera setup for image with calibration