Cloud-based task planning for smart robots

Abstract

This paper proposes an Open Semantic Framework for knowledge acquisition of cognitive robots performing manipulation tasks. It integrates a Cloud-based Engine, which extracts discriminative features from the objects and generates their manipulation actions, and an Ontology, where the Engine saves data for future accesses. The Engine offloads robots by transferring computation on the Cloud. The Ontology favors knowledge sharing among manipulator robots by defining a common manipulation vocabulary. It extends the work proposed by the IEEE RAS Ontology for Robotics and Automation Working Group by covering the manipulation task domain. During ontological data insertion, data duplication is avoided by providing a novel efficient interlinking algorithm. During their retrieval, visual data processing is optimized by using a cascade hashing algorithm that intelligently accesses data. No training is required for object recognition and manipulation because of the adoption of a human-robot cooperation. The framework is based on the open-source Robot Operating System.