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N-learning: An Approach for Learning and Teaching Skills in Multirobot Teams

Published online by Cambridge University Press:  16 April 2019

Luís Feliphe S. Costa
Department of Computer Engineering and Automation, Universidade Federal do Rio Grande do Norte, Natal, Brazil. E-mails:,
Tiago P. Nascimento*
Department of Computer Systems, Universidade Federal da Paraiba, Paraiba, Brazil
Rosiery da S. Maia
Department of Informatics, Universidade do Estado do Rio Grande do Norte Mossoró, Brazil. E-mail:
Luiz Marcos G. Gonçalves
Department of Computer Engineering and Automation, Universidade Federal do Rio Grande do Norte, Natal, Brazil. E-mails:,
*Corresponding author. E-mail:


We propose the N-learning practical approach for teaching and learning behaviors in a multirobot system, which is performed through mandatory behavior acquisition based on interactions between the robots at execution time. The proposed methodology can be used to self-program the robots of a team by programming only a single robot with a set of codes that contain behaviors to be transferred and used by other robots as necessary. These codes are implemented in a modular fashion. An advantage of our approach is that when a team of robots is required to perform a specific mission, the set of behaviors required to accomplish that mission can be implemented only once in a single robot or in a distributed fashion. Then, these distributed behaviors are transferred to each of the other robots in the team according to their demand, without the need to reprogram them by hand since the robots in the team can share them autonomously. As an application example, a human critic can teach (or program) only one or a few robots, and these robots are thus able to exchange knowledge with the other team members since they have been preinstalled to run the N-learning system basics. Simulated and real robot experiments are performed to demonstrate the feasibility and validation of our approach.

© Cambridge University Press 2019 

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