The sample characterization
The purpose of the revisit node experiment is to collect a sample sensor characterization of a meetpoint in the environment.
For the robot this means accessing the GVG, tracing an edge, and homing, probing, homing to equidistance at the meetpoint.
The data resulting from a single characterization consists of the local minima coordinates relative to the robot position.
These coordinates are then used to compute the corresponding minima distances and relative edge angles at the meetpoint.
In the figure below, line segment notation refers to the minima distances, while relative edge angles are simply numbered.
The complete meetpoint
In order to characterize a meetpoint, samples are taken arrival number times for every edge of the meetpoint (the degree of the meetpoint).
For example, collecting 10 samples of a meetpoint occuring at an intersection of three hallway directions would be characterized by 30 samples in total.
This example is illustrated in the figure below.
The data analysis
By collecting all of the minima distance values together we are able to calculate an overall mean and standard deviation.
Similarly, we may calculate the standard deviation of the mean minima distances per sample, which is less than the overall standard deviation.
For a given meetpoint we refer to the standard deviation of mean minima distance values as SIGMA_DIST.
In the first figure below, the blue bars are histogram plots of minima distance values.
In the second figure the blue bars represent the mean minima distances per sample.
Both figures show red vertical lines at the mean. The yellow and green lines are shown at n-sigma distances from the mean, where n ranges from 1 to 4.
The relative edge angles are computed from the sample edge angle values. Using as reference the symmetric division
for a given meetpoint degree, we can then compute angle differences from symmetry for each sample.
The sum of these differences gives a single value per sample.
We then compute the overall mean and standard deviation of these symmetric differences.
For a given meetpoint we refer to the standard deviation of all symmetric angle differences means as SIGMA_SYM.
In the first figure below, the blue bars represent the histogram of symmetric angle differences from every edge angle.
In the second figure the blue bars represent the histogram of the sums of symmetric differences from every sample.
Both figures show red vertical lines at the mean. The yellow and green lines are shown at n-sigma distances from the mean, where n ranges from 1 to 4.
