A review and comparison of ontology-based approaches to robot autonomy

Within the next decades, robots will need to be able to execute a large variety of tasks autonomously in a large variety of environments. To relax the resulting programming effort, a knowledge-enabled approach to robot programming can be adopted to organize information in re-usable knowledge pieces. However, for the ease of reuse, there needs to be an agreement on the meaning of terms. A common approach is to represent these terms using ontology languages that conceptualize the respective domain. In this work, we will review projects that use ontologies to support robot autonomy. We will systematically search for projects that fulfill a set of inclusion criteria and compare them with each other with respect to the scope of their ontology, what types of cognitive capabilities are supported by the use of ontologies, and which is their application domain.Peer ReviewedPostprint (author's final draft

Declarative-knowledge-based reconfiguration of automation systems using a blackboard architecture

This article describes results of the work on knowledge representation techniques chosen for use in the European project SIARAS (Skill-Based Inspection and Assembly for Reconfigurable Automation Systems). Its goal was to create intelligent support system for reconfiguration and adaptation of robot-based manufacturing cells. Declarative knowledge is represented first of all in an ontology expressed in OWL, for a generic taxonomical reasoning, and in a number of special-purpose reasoning modules, specific for the application domain. The domain/dependent modules are organized in a blackboard-like architecture

An ontology-based approach for integrating engineering workflows for industrial assembly automation systems

Modern manufacturing organisations face a number of external challenges as the customer-base is more varied, more knowledgeable, and has a broader range of requirements. This has given rise to paradigms such as mass customisation and product personalisation. Internally, businesses must manage multidisciplinary teams that must work together to achieve a common goal despite spanning multiple domains, organisations, and due to improved communication technologies, countries. The motivation for this research is to therefore understand firstly how the multiplicity of stakeholders come together to realise the ever increasing and ever more complex number of product variants that manufacturing systems must now realise. The lack of integration of engineering tools and methods is identified to be one of the barriers to smooth engineering workflows and thus one of the key challenges faced in the current dynamic market. To address this problem, this research builds upon previous works that propose domain ontologies for representing knowledge in a way that is both machine and human readable, facilitating interoperability between engineering software. In addition to this, the research develops a novel Skill model that brings the domain ontologies into a practical, implementable framework that complements existing industrial workflows. The focus of this thesis is the domain of industrial assembly automation systems due to the role this stage of manufacturing plays in realising product variety. Therefore, the proposed ontological models and framework are applied to product assembly scenarios. The key contributions of this work are the consolidation of domain ontologies with a Skill model within the context of assembly systems engineering, development of a broader framework for the ontologies to sit within that complements existing workflows. In addition, the research demonstrates how the framework can be applied to connect assembly process planning activities with machine control logic to identify and rectify inconsistencies as new products are introduced. In summary, the thesis identifies the shortcomings of existing ontological models within the context of manufacturing, develops new models to address those shortcoming, and develops new, useful ways for ontological models to be used to address industrial problems by integrating them with virtual engineering tools