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. 2022 Mar 7;9:720448. doi: 10.3389/frobt.2022.720448

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Copyright © 2022 Bertacchini, Scuro, Pantano and Bilotta.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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For developing the learning machine in Mathematica, a training set of photos for face recognition was created. Through the command “SetDirectory” the photos of a person of the group were imported and the face acquisition procedure was carried out with the function “FindFaces”. This procedure is repeated in the program for all classes of persons to be recognised by the robot. The last step is programming in Choregraphe. Using the “Face Detection” and “Take a Picture” blocks, the NAO searches for a face in the environment and takes a picture of she/he. These photos are saved in the NAO’s internal memory, passed to Mathematica and processed. The response file given by Mathematica is passed to Choreographe thanks to the “Get Attached” block. The file is read by “Get String”, programmed specifically in Python, and then played back through “Say Text".