ONA for Autonomous ROS-Based Robots

Abstract

In this paper we will show that OpenNARS for Applications (ONA) can be used for enhanced autonomous robots operating in the real world. It is done by utilizing state-of-the-art object detection along with Simultaneous Localization and Mapping techniques while inheriting the strengths of means-end reasoning and adding robust learning at runtime into the picture. This is showcased in an experiment where an ONA-controlled mobile robot with manipulator arm is learning about its environment to collect bottles to be returned to a human operator.