Embedded Neural Network for Swarm Learning of Physical Robots

Pitoyo Hartono, Sachiko Kakita

Abstract: In this study we ran real time learning of multiple physical autonomous robots situated in a real dynamic environment. Each robot has an onboard micro controller where a simple neural network is embedded. The neural network was built with the consideration of the power and calculation resources limitation which is a general characteristic of simple robots. In the experiments, several autonomous robots were placed in one environment, where each of them was given a specific task which was expressed as the evaluation function for the robot’s neural network. The learning processes of the robots were started simultaneously from their randomized initial conditions. The presence of several robots consequently formed a dynamic environment, in which an action of one robot affected the learning process of others. We demonstrated the efficiency of the embedded learning mechanism with respect to different environmental factors.