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AutomaticOntology-basedPlanGeneration foranIndustrialRoboticsSystem
TimonHoebert,WilfriedLepuschitz,MunirMerdan
PracticalRobotics InstituteAustria
{hoebert,lepuschitz,merdan}@pria.at
Abstract. Programming and re-configuration of
robots are associated with high costs, especially for
small- and medium-sized enterprises. We present an
ontology-driven solution that can automate the con-
figuration as well as the generation of process plans
and schedules thereby significantly lowering the ef-
forts in thecaseof changes. Thepresentedapproach
is demonstrated in a laboratory environment with an
industrialpilot test case.
1. Introduction
Robotics technology, which can prove high effi-
ciency, precision, and repeatability, is regarded as a
viable solution to cope with the increasing number
of individualized products. However, robot systems
still often do not meet the demands of small- and
medium-sized enterprises (SMEs) [8]. Especially,
since the programming of industrial robots is com-
plex and time-consuming. To be able to dynami-
cally adapt to new products, robotic systems need to
work autonomously. Autonomous systems, in this
context,meansthatrobotssystemscanperformhigh-
level taskspecificationswithoutexplicitlybeingpro-
grammed [2]. To reach specific goals, such systems
shouldbeable to receivegoalsandautomatically se-
quenceplansandexecute themconsidering theircur-
rent state. In our previous work, we presented the
control architecture for industrial robots, which can
generate actions based on an product model by link-
ing product model, manufacturing process, and pro-
ductionenvironmentinanontology[7]. Inthispaper,
we focus on the automated plan generation from the
ontology and present an approach for flexibly cou-
pling of the decision-making mechanism and ontol-
ogy.
In section 2, we will detail the architecture and im-
plementation. Finally, Section 3 concludes the paper
with a summary and an outlook on further research issues.
2.Architecture
The industrial robot control layer responsible for
the management of the robotics systems consists of
a World-Model and a Decision-Making component.
The decision-making mechanism (Planner) acts as
a link between the semantic model of the produc-
tion environment and the available robot system ca-
pabilities. The World Model contains the semantic
representation of the relevant objects in the robotics
system including their properties and relations. The
Planning Domain Definition Language (PDDL) is
used for decision-making and the world model is
conceptually defined using the Web Ontology Lan-
guage(OWL)standard. In thiscontext,wetransform
robotics domain knowledge represented in OWL to
PDDL as a targeted mechanism for planning. Multi-
ple applied robotic systems use PDDL for task plan-
ning and a lot of work has been done in combining
ontologies and AI planning base [5, 1]. Especially
ROSPlan[4], aROSimplementation, is acommonly
used implementation for this purpose. Based on
ROSPlan, OWL-ROSPlan [3] extends this approach
using a specialized OWL-Ontology as knowledge-
base instead of traditional databases. The disadvan-
tage of these approaches is the implementation ef-
fort for application. Even OWL-ROSPlan requires
a predefined data format of the ontology. Our work
extends this research by automating the translation
of the input required by PDDL from the ontology as
well as fromthePDDLback to theontologywithout
anypredefinedontology formats.
2.1.OWL-PDDLMappingscheme
ThebasicbuildingblocksofOWL,aretriplescon-
sisting of subject, predicate, and object. The ba-
sic building blocks of PDDL are actions and PDDL-
predicates. To avoid confusion of the two different
27
Joint Austrian Computer Vision and Robotics Workshop 2020
- Title
- Joint Austrian Computer Vision and Robotics Workshop 2020
- Editor
- Graz University of Technology
- Location
- Graz
- Date
- 2020
- Language
- English
- License
- CC BY 4.0
- ISBN
- 978-3-85125-752-6
- Size
- 21.0 x 29.7 cm
- Pages
- 188
- Categories
- Informatik
- Technik