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:vGripper2 r:isFree “true”^^xsd:boolean.
:part23 ro:movable :vGripper2.
:part23 r:connects :part54, :part64.
(r:connects :part23 :part54 :part64)
(r:movable :part23 :vGripper2)
(r:isFree :vGripper2)
subject predicate object1
subject(predicate [object1] [, objectN].
[objectN])
3...
...
Figure 1. Mapping OWL triples with PDDL predicates.
Also, three examples of different parameter length are
shown.
types of predicates, the latter ones are only referred
to as PDDL-Predicates. The general idea of this ap-
proachis theequalizationofbothbuildingblocks, re-
lating triples with PDDL-predicates. Using a similar
approach like WebPDDL [6], OWL-IRIs are used as
PDDL-predicatenamestoidentifythedatadistinctly.
OWL-predicates relate subjects and objects, as
verbs do in sentences, but PDDL-predicates are only
binarystatements relating tomultipleobjectparame-
ters. In practice, PDDL-predicates usually only have
one or two object parameters, which can be seen as
subjectandobject. Thecompletemappingschemeis
illustrated with three examples in Figure 1. PDDL-
predicates with only one parameter are mapped to
boolean-valued objects triples. In practice, PDDL-
predicates with more than two parameters are rare
because of their complexity (only 4 percent of all
predicates from all IPC (1998-2018) domains. But,
even these PDDL-predicates can be simplified to
multiple PDDL-predicateswith twoparameters.
2.2.SemanticPDDLGeneration
The system automatically generates the PDDL3-
problem for the planner based on the information in
the ontology and PDDL-domain. This enables easy
and extensible programming of the system. Theuser
only has to specify the PDDL-domain with IRIs as
PDDL-predicate names and add the goal as triples
into a separate part (separate graph) of the ontol-
ogy database. The system automatically queries
all triples of NamedIndividuals regarding this pred-
icates, maps them to PDDL-predicates as mentioned
earlierandaddsthemtotheinitsectioninthePDDL-
problem. These queries are executed in parallel, and
the particular subjects are recorded. After query-
ing the triples, the OWL-types of the recorded sub-
jectsaresearchedintheontologyandwrittenintothe
PDDL-problem. Since each NamedIndividual can have multiple parent-classes, but not all are relevant
forplanning,only theoneswhicharespecified in the
PDDL-domainareused.
3.Conclusion
The proposed knowledge-driven approach simpli-
fies the programming efforts of the industrial robot.
The code for the industrial implementation is gener-
ated automatically based on the defined rules, states
and actions. A system engineer only needs to de-
scribe the functionality of the assembly line or char-
acteristics of the product to be assembled, without
having to consider further engineering issues. In
our application, we successfully used the developed
mechanism for planning pick-and-place operations
ofanindustryrobotbyKukaaswellas theFestopor-
talrobot,whenjointlyappliedforassemblingofPCB
boards. As future work, we aim to consider product
assemblytasksinvolvingmorecomplexproductsand
production layouts.
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Joint Austrian Computer Vision and Robotics Workshop 2020
- Titel
- Joint Austrian Computer Vision and Robotics Workshop 2020
- Herausgeber
- Graz University of Technology
- Ort
- Graz
- Datum
- 2020
- Sprache
- englisch
- Lizenz
- CC BY 4.0
- ISBN
- 978-3-85125-752-6
- Abmessungen
- 21.0 x 29.7 cm
- Seiten
- 188
- Kategorien
- Informatik
- Technik