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Reasoning and state monitoring for the robust execution of robotic manipulation tasks
dc.contributor.author | Ruiz Celada, Oriol |
dc.contributor.author | Rosell Gratacòs, Jan |
dc.contributor.author | Diab, Mohammed |
dc.contributor.other | Universitat Politècnica de Catalunya. Institut d'Organització i Control de Sistemes Industrials |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial |
dc.date.accessioned | 2022-11-04T12:20:19Z |
dc.date.issued | 2022 |
dc.identifier.citation | Ruiz, O.; Rosell, J.; Diab, M. Reasoning and state monitoring for the robust execution of robotic manipulation tasks. A: IEEE International Conference on Emerging Technologies and Factory Automation. "Proceedings of the 2022 IEEE 27th International Conference on Emerging Technologies and Factory Automation". Institute of Electrical and Electronics Engineers (IEEE), 2022, p. 1-4. DOI 10.1109/ETFA52439.2022.9921634. |
dc.identifier.uri | http://hdl.handle.net/2117/375675 |
dc.description.abstract | The execution of robotic manipulation tasks needs to be robust in front of failures or changes in the environment, and for this purpose, Behavior Trees (BT) are a good alternative to Finite State Machines, because the ability of BTs to be edited during run time and the fact that one can design reactive systems with BTs, makes the BT executor a robust execution manager. However, the good monitoring of the system state is required in order to react to errors at either geometric or symbolic level requiring, respectively, replanning at motion or at task level. This paper make a proposal in this line and, moreover, makes task planning adaptive to the actual situations encountered by knowledge-based reasoning procedures to automatically generate the Planning Domain Definition Language (PDDL) files that define the task. |
dc.format.extent | 4 p. |
dc.language.iso | eng |
dc.publisher | Institute of Electrical and Electronics Engineers (IEEE) |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 International |
dc.rights | © 2021 IEEE |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ |
dc.subject | Àrees temàtiques de la UPC::Física |
dc.subject.lcsh | Robots--Control systems |
dc.subject.other | Robotic manipulation |
dc.subject.other | Task planning |
dc.subject.other | Task monitoring |
dc.subject.other | Reasoning |
dc.subject.other | Ontology |
dc.subject.other | Automata |
dc.subject.other | Monitoring |
dc.title | Reasoning and state monitoring for the robust execution of robotic manipulation tasks |
dc.type | Conference lecture |
dc.subject.lemac | Robots--Sistemes de control |
dc.identifier.doi | 10.1109/ETFA52439.2022.9921634 |
dc.description.peerreviewed | Peer Reviewed |
dc.relation.publisherversion | https://ieeexplore.ieee.org/document/9921634 |
dc.rights.access | Open Access |
local.identifier.drac | 34336320 |
dc.description.version | Postprint (published version) |
dc.date.lift | 10000-01-01 |
local.citation.author | Ruiz, O.; Rosell, J.; Diab, M. |
local.citation.contributor | IEEE International Conference on Emerging Technologies and Factory Automation |
local.citation.publicationName | Proceedings of the 2022 IEEE 27th International Conference on Emerging Technologies and Factory Automation |
local.citation.startingPage | 1 |
local.citation.endingPage | 4 |