On planning in a knowledge-hypergraph
conference paper
Autonomous robots that operate in indoor, uncertain environments move around from one location to the next to fulfill a set of ordered task. To do so, they need a floor plan of the building to plan their route. In case the building is unfamiliar to a robot it can employ online mapping techniques, though these techniques are resource intensive and time consuming. In addition, processing such geometric maps in an automated planner to determine a feasible route is resource demanding as well. The solution proposed in this article is an ontology that combines knowledge of floor plans and actual information of a building with concepts in automated planning, so that robots become more efficient in route planning. Moreover, the ontology is implemented as a hypergraph to benefit from its advances in creating elegant inference-rules, e.g., to infer route-alternatives while preparing the operation.
Topics
TNO Identifier
955331
ISSN
16130073
Publisher
CEUR-WS
Source title
CEUR Workshop Proceedings, 2020 Joint Ontology Workshops, JOWO 2020, 31 August 2020 through 7 October 2020
Pages
0-0