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Implementation of NAO robot maze navigation based on computer vision and collaborative learning.

Magall�n-Ram�rez, Daniela; Mart�nez-Aguilar, Jorge David; Rodr�guez-Tirado, Areli; Balderas, David; L�pez-Caudana, Edgar Omar; Moreno-Garc�a, Carlos Francisco


Daniela Magall�n-Ram�rez

Jorge David Mart�nez-Aguilar

Areli Rodr�guez-Tirado

David Balderas

Edgar Omar L�pez-Caudana


Maze navigation using one or more robots has become a recurring challenge in scientific literature and real life practice, with fleets having to find faster and better ways to navigate environments such as a travel hub, airports, or for evacuation of disaster zones. Many methodologies have been explored to solve this issue, including the implementation of a variety of sensors and other signal receiving systems. Most interestingly, camera-based techniques have become more popular in this kind of scenarios, given their robustness and scalability. In this paper, we implement an end-to-end strategy to address this scenario, allowing a robot to solve a maze in an autonomous way, by using computer vision and path planning. In addition, this robot shares the generated knowledge to another by means of communication protocols, having to adapt its mechanical characteristics to be capable of solving the same challenge. The paper presents experimental validation of the four components of this solution, namely camera calibration, maze mapping, path planning and robot communication. Finally, we showcase some initial experimentation in a pair of robots with different mechanical characteristics. Further implementations of this work include communicating the robots for other tasks, such as teaching assistance, remote classes, and other innovations in higher education.


MAGALLÁN-RAMÍREZ, D., MARTÍNEZ-AGUILAR, J.D., RODRÍGUEZ-TIRADO, A., BALDERAS, D., LÓPEZ-CAUDANA, E.O. AND MORENO-GARCÍA, C.F. 2022. Implementation of NAO robot maze navigation based on computer vision and collaborative learning. Frontiers in robotics and AI [online], 9, article 834021. Available from:

Journal Article Type Article
Acceptance Date Mar 7, 2022
Online Publication Date Apr 4, 2022
Publication Date Apr 30, 2022
Deposit Date Apr 4, 2022
Publicly Available Date Apr 5, 2022
Journal Frontiers in Robotics and AI
Electronic ISSN 2296-9144
Publisher Frontiers Media
Peer Reviewed Peer Reviewed
Volume 9
Article Number 834021
Keywords Robot navigation; Computer vision; Mapping; NAO robot; Educational innovation
Public URL
Additional Information A pre-print version of this article was first available as: MAGALLÁN-RAMIREZ, D., RODRIGUEZ-TIRADO, A., MARTÍNEZ-AGUILAR, J.D., MORENO-GARCÍA, C.F., BALDERAS, D. and LÓPEZ-CAUDANA, E.O. 2021. Implementation of NAO robot maze navigation based on computer vision and collaborative learning. Preprints [online]. Available from:


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