Application of fuzzy logic in learning autonomous robots systems

Abstract

Autonomous Robots Systems (ARS) can learn by establishing plans, executing them in a given environment and analyzing the results of the execution. The logic used among this process is usually the classic logic, which most of the times ends up being too restrictive and not consistent with the world the ARS is facing. This paper proposes the application of fuzzy logic to address this issue and improve the ARS learning curve considerably. © 2013 Springer-Verlag.