Ontology-based Approaches to Robot Autonomy

A landscape of current research

About this page

This page presents different projects that use explicit knowledge encoded in an ontology to support some aspects of robot autonomy. Robots may reach different levels of autonomy depending on what restrictions their architecture imposes, and what type of cognitive capabilities it supports. It is hard, however, to pinpoint a definition of autonomy. It is more common to list features that a cognitive system needs to address, such as:

  • recognition and categorization;
  • decision making and choice;
  • perception and situation assessment;
  • prediction and monitoring;
  • problem solving and planning;
  • reasoning and belief maintenance;
  • execution and action; and
  • remembering, reflection, and learning.

This page has been created to summarize the findings of the literature review paper entitled "A Review and Comparison of Ontology-based Approaches to Robot Autonomy" that was published at the Knowledge Engineering Review journal in 2019.

This is the abstract of the paper:

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 re-use, 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.

Please use the following bibtex entry for citing us:


In total, six frameworks/projects have been subject of study in our review. For each of them, their underlying principles and foundations are discussed, as well as what application domain the system was designed for. We also describe how the frameworks evolved over time, and what impact they have had so far. The selection of the presented projects has been done based on the selection criteria presented within the article. To the best of our knowledge, we have included all projects that satisfy the criteria.

CARESSES (2017-)

Department of Informatics, Bioengineering, Robotics, and Systems Engineering, University of Genoa

Project Website Maintainer Website Source Code

PMK (2019-)

Institute of Industrial and Control Engineering (IOC), Polytechnic University of Catalonia (UPC)

Project Website Maintainer Website Source Code

ORO (2010-)


Project Website Maintainer Website Source Code

KnowRob (2009-)

Institute for Artificial Intelligence, University of Bremen

Project Website Maintainer Website Source Code

ROSETTA (2013-)

Computer Science, Faculty of Engineering of Lund University

Project Website Maintainer Website Source Code

OROSU (2013-)

Polytechnic Institute of Castelo Branco, Portugal

Project Website Maintainer Website Source Code

Cognitive Capabilities

The scope of reasoning is our second classification criterion for the comparison between ontology-based approaches in autonomous robotics. It consists of a categorization of nine ontology-based reasoning tasks that are in particular relevant for autonomous robotics, and that have been considered in previous works.

Recognition and Categorization

Decision Making and Choice

Perception and Situation Assessment

Prediction and Monitoring

Problem Solving and Planning

Reasoning and Belief Maintenance

Execution and Action

Interaction and Communication

Remembering, Reflection, and Learning

Contact us

Should you have any doubt/comment about our work, please, do not hesitate to contact us.

Alberto Olivares-Alarcos - aolivares@iri.upc.edu
Daniel Beßler - danielb@uni-bremen.de