Implementation of a Decision Making Algorithm Based on Somatic Markers on the Nao Robot

Abstract

Decision making is an essential part of Autonomous Mobile Systems. Research shows that emotion is an important factor in human decision making. Therefore an increasing number of approaches using modelled emotions for decision making are developed for artificial intelligent systems. Often those approaches are only evaluated in simulated environments in which dummies are used to represent actions. However, the realisation of a real robot application also requires the handling of problems which may not occur in a simulated environment, such as long execution times. Furthermore, the adaption of existing approaches to variant applications often includes several time-consuming adjustments to the system. In this paper the implementation of an emotional decision making algorithm for the Nao robot is presented. The implementation design is based on the human brain structure and models different brain parts which are included in the decision making process. Beside the fact that the chosen structure is closer to the human model, the modular architecture allows an easy implementation of enhancements or different approaches. A key point is the easy adaption of the approach to different applications, suitable even for users without technical expertise or programming skills. As an example, a possible real life scenario is used, in which the robot is embedded in a social environment.