Browsing by Author "Bebler, Daniel"
Now showing items 1-4 of 4
-
A review and comparison of ontology-based approaches to robot autonomy
Olivares Alarcos, Alberto; Bebler, Daniel; Khamis, Alaa; Goncalves, Paulo; Habib, Maki K.; Bermejo Alonso, Julita; Barreto, Marcoss; Diab, Mohammed; Rosell Gratacòs, Jan; Quintas, João; Olszewska, Joanna; Nakawala, Hirenkumar; Pignaton de Freitas, Edison; Gyrard, Amelie; Borgo, Stefano; Alenyà Ribas, Guillem; Beetz, Michael; Li, Howard (2019-01-01)
Article
Open AccessWithin 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 ... -
An ontology for failure interpretation in automated planning and execution
Diab, Mohammed; Pomarlan, Mihai; Bebler, Daniel; Akbari, Aliakbar; Bateman, John; Beetz, Michael; Rosell Gratacòs, Jan (2019)
Conference lecture
Open AccessAutonomous indoor robots are supposed to accomplish tasks, like serve a cup, which involve manipulation actions, where task and motion planning levels are coupled. In both planning levels and execution phase, several source ... -
FailRecOnt - An ontology-based framework for failure interpretation and recovery in planning and execution
Diab, Mohammed; Pomarlan, Mihai; Borgo, Stefano; Bebler, Daniel; Rosell Gratacòs, Jan; Bateman, John; Beetz, Michael (2021)
Conference report
Open AccessAutonomous mobile robot manipulators have the potential to act as robot helpers at home to improve quality of life for various user populations, such as elderly or handicapped people, or to act as robot co-workers on factory ... -
“Knowing from” – An outlook on ontology enabled knowledge transfer for robotic systems
Diab, Mohammed; Pomerlan, Mihai; Bebler, Daniel; Rosell Gratacòs, Jan (2020)
Conference report
Open AccessEncoding practical knowledge about everyday activities has proven difficult, and is a limiting factor in the progress of autonomous robotics. Learning approaches, e.g. imitation learning from human data, have been used as ...