The Exchange of Knowledge Using Cloud Robotics

Abstract

To enable robots to perform human-level tasks flexibly in varying conditions, we need a mechanism that allows them to exchange knowledge between themselves for crowd-sourcing the knowledge gap problem. One approach to achieve this is to equip a cloud application with a range of encyclopedic knowledge (i.e., ontologies) and execution logs of different robots performing the same tasks in different environments. In this letter, we show how knowledge exchange between robots can be done using openEASE as the cloud application. We equipped openEASE with ontologies about the kitchen domain, execution logs of three robots operating in two different kitchens, and semantic descriptions of both environments. By addressing two different use cases, we show that two PR2 robots and one Fetch robot can successfully adapt each other's plan parameters and subsymbolic data to the experiments that they are conducting.