A mobile robot based on real-time reinforcement learning using human evaluation

Abstract

In develping intelligent robot systems, it is necessary for designers to make robots by fine-tuning parameters and modifying programs in detail. However, this conventional method is a big burden not only for designers but also general users. In this paper, we present a new design method based on reinforcement learning in real time through human-robot interaction. We also develop an autonomous mobile robot system and show its possibilities.