Publication
A novel framework to improve motion planning of robotic systems through semantic knowledge-based reasoning
| dc.contributor.author | Bernardo, Rodrigo | |
| dc.contributor.author | Sousa, João M.C. | |
| dc.contributor.author | Gonçalves, Paulo | |
| dc.date.accessioned | 2023-07-07T12:26:20Z | |
| dc.date.available | 2023-07-07T12:26:20Z | |
| dc.date.issued | 2023 | |
| dc.description.abstract | The need to improve motion planning techniques for manipulator robots, and new effective strategies to manipulate different objects to perform more complex tasks, is crucial for various real-world applications where robots cooperate with humans. This paper proposes a novel framework that aims to improve the motion planning of a robotic agent (a manipulator robot) through semantic knowledge-based reasoning. The Semantic Web Rule Language (SWRL) was used to infer new knowledge based on the known environment and the robotic system. Ontological knowledge, e.g., semantic maps, were generated through a deep neural network, trained to detect and classify objects in the environment where the robotic agent performs. Manipulation constraints were deduced, and the environment corresponding to the agent’s manipulation workspace was created so the planner could interpret it to generate a collision-free path. For reasoning with the ontology, different SPARQL queries were used. The proposed framework was implemented and validated in a real experimental setup, using the planning framework ROSPlan to perform the planning tasks. The proposed framework proved to be a promising strategy to improve motion planning of robotics systems, showing the benefits of artificial intelligence, for knowledge representation and reasoning in robotics. | pt_PT |
| dc.description.version | info:eu-repo/semantics/publishedVersion | pt_PT |
| dc.identifier.citation | Bernardo, R., Sousa, J. M., & Gonçalves, P. J. (2023). A novel framework to improve motion planning of robotic systems through semantic knowledge-based reasoning. Computers & Industrial Engineering. DOI 10.1016/j.cie.2023.109345 | pt_PT |
| dc.identifier.doi | 10.1016/j.cie.2023.109345 | pt_PT |
| dc.identifier.uri | http://hdl.handle.net/10400.11/8554 | |
| dc.language.iso | eng | pt_PT |
| dc.peerreviewed | yes | pt_PT |
| dc.publisher | Elsevier | pt_PT |
| dc.relation | FCT - Foundation for Science and Technology, Portugal, I.P., through IDMEC, under LAETA, project UIDB/50022/2020 | pt_PT |
| dc.relation | PhD Scholarship BD\6841\2020 from FCT, Portugal | pt_PT |
| dc.relation | project 0770_EUROAGE2_4_E (POCTEP Programa Interreg V-A Spain-Portugal) | pt_PT |
| dc.relation | European Union’s Horizon 2020 programme under StandICT.eu 2023 (under Grant Agreement No.: 951972) | pt_PT |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | pt_PT |
| dc.subject | Knowledge representation | pt_PT |
| dc.subject | Ontologies | pt_PT |
| dc.subject | Manipulation | pt_PT |
| dc.subject | Motion planning | pt_PT |
| dc.subject | Semantic maps | pt_PT |
| dc.title | A novel framework to improve motion planning of robotic systems through semantic knowledge-based reasoning | pt_PT |
| dc.type | journal article | |
| dspace.entity.type | Publication | |
| oaire.citation.startPage | 109345 | pt_PT |
| oaire.citation.title | Computers & Industrial Engineering | pt_PT |
| oaire.citation.volume | 182 | pt_PT |
| person.familyName | Gonçalves | |
| person.givenName | Paulo | |
| person.identifier.ciencia-id | 2816-A2FA-C5A3 | |
| person.identifier.orcid | 0000-0002-8692-7338 | |
| person.identifier.rid | E-5640-2012 | |
| person.identifier.scopus-author-id | 35853838000 | |
| rcaap.rights | openAccess | pt_PT |
| rcaap.type | article | pt_PT |
| relation.isAuthorOfPublication | 86a6a234-d690-4c2b-8bee-d58005eebba2 | |
| relation.isAuthorOfPublication.latestForDiscovery | 86a6a234-d690-4c2b-8bee-d58005eebba2 |