Implementation of NAO robot maze navigation based on computer vision and collaborative learning.
Dr Carlos Moreno-Garcia firstname.lastname@example.org
Senior Lecturer (A)
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: https://doi.org/10.3389/frobt.2022.834021
|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|
|Peer Reviewed||Peer Reviewed|
|Keywords||Robot navigation; Computer vision; Mapping; NAO robot; Educational innovation|
|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: https://doi.org/0.20944/preprints202106.0037.v1|
MAGALLAN-RAMIREZ 2022 Implementation of NAO (VOR)
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