Author:
Julita Bermejo-Alonso
Affiliation:
UPM Autonomous Systems Laboratory (ASLab) c/José Gutiérrez Abascal, 2, 28006 Madrid and Spain
Keyword(s):
Task Ontologies, Planning Ontologies, Ontological Engineering, Autonomous Systems.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Data Engineering
;
Domain Analysis and Modeling
;
Enterprise Information Systems
;
Information Systems Analysis and Specification
;
Knowledge Engineering and Ontology Development
;
Knowledge Representation
;
Knowledge-Based Systems
;
Ontologies and the Semantic Web
;
Ontology Engineering
;
Symbolic Systems
Abstract:
Bermejo-Alonso and colleagues (Bermejo-Alonso et al., 2018) define an ontology for tasks and planning in the autonomous system domain. It focuses on an emergency scenario for Unmanned Ground Vehicles (UGVs) or Unmanned Aerial Vehicles (UAVs). In this context, it is necessary to define how the autonomous system will act, detailing how the actions should be done to achieve system goals. The planning process starts with detailing the planning domain knowledge: the initial state, the goals, the actors, the resources, etc. This domain knowledge is then fed into a planner that, if a solution exists, will produce a plan or a set of plans to be used by the robotic system. Ontologies are a useful way to provide this domain knowledge and can be used to characterise the planning domain knowledge. However, there is a number of available ontologies for planning, being unclear which one is best for autonomous systems. This paper presents a review of existing task and planning vocabularies, taxonom
ies and ontologies, as a necessary first step in an ontology engineering process that addressed the autonomous system planning needs. This paper describes the analised ontologies, their main features, and how the process to integrate them was carried out.
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