Update sensor/docs/tutorials/tag_based_pnp_calibrator.md

Co-authored-by: Kenzo Lobos Tsunekawa <[email protected]>

sensor/docs/tutorials/tag_based_pnp_calibrator.md

@@ -142,7 +142,7 @@ The images below show that with the calibrated transformation, the projected poi
 
 - Why does the reprojection error increase when more data is collected?
 
-  1. When there are few samples, the model will fit the available data the best it can, even in the presence of noise (over-fitting). The more data is collected, the error may increase to a certain extent, but that is the model trying to fit all the data, being unable to fit the noise. However, it should reach a more-or-less table peak with about 10-15 pairs (depending on the data collection pattern/sampling).
+  1. When there are few samples, the model will fit the available data the best it can, even in the presence of noise (over-fitting). The more data is collected, the error may increase to a certain extent, but that corresponds to the model attempting to fit all the data, this time unable to fit the noise, resulting in a higher error. However, it should reach a more-or-less table peak with about 10-15 pairs (depending on the data collection pattern/sampling).
 
 - Why doesn't the reprojection error seem low enough?