Simplified Q-learning for holonomic mobile robot navigation

Abstract

In this paper we propose a method of presenting a special case of Value Function as a solution to POMDP in holonomic mobile robot navigation. By using this new method the Value Function complexity will be reduced and more intuitive. The result of this new Value Function is validated with particle filter simulation in Matlab and also experimented physically using a simple autonomous mobile robot built with Lego Mindstorms NXT with 3 ultrasonic sonar and RWTH Mindstorms NXT Toolbox for Matlab to connect the robot to Matlab. This simulation and experiment also incorporate particle filter localization from previous research. The simulation and experiment show that the Value Function can be utilized very well.