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dc.contributor.authorBatista, Josias Guimarães-
dc.contributor.authorVasconcelos, Felipe José de Sousa-
dc.contributor.authorRamos, Kaio Martins-
dc.contributor.authorSouza, Darielson Araújo de-
dc.contributor.authorSilva, José Leonardo Nunes da-
dc.date.accessioned2022-04-18T13:23:00Z-
dc.date.available2022-04-18T13:23:00Z-
dc.date.issued2020-
dc.identifier.citationBATISTA, Josias Guimarães; VASCONCELOS, Felipe José de Sousa; RAMOS, Kaio Martins; SOUZA, Darielson Araújo de; SILVA, José Leonardo Nunes da. Path planning collision avoidance using reinforcement learning. In: CONGRESSO BRASILEIRO DE AUTOMÁTICA, XXIII., 23 e 26 de Novembro de 2020, Online. Anais[…], Campinas, Galoá, v. 2 , n. 1, 2020. CBA2020. DOI: 10.48011/asba.v2i1.1597pt_BR
dc.identifier.issn2525-8311-
dc.identifier.otherDOI: https://doi.org/10.48011/asba.v2i1.1597-
dc.identifier.urihttp://www.repositorio.ufc.br/handle/riufc/65101-
dc.description.abstractIndustrial robots have grown over the years making production systems more and more efficient, requiring the need for efficient trajectory generation algorithms that optimize and, if possible, generate collision-free trajectories without interrupting the production process. In this work is presented the use of Reinforcement Learning (RL), based on the Q-Learning algorithm, in the trajectory generation of a robotic manipulator and also a comparison of its use with and without constraints of the manipulator kinematics, in order to generate collisionfree trajectories. The results of the simulations are presented with respect to the efficiency of the algorithm and its use in trajectory generation, a comparison of the computational cost for the use of constraints is also presented.pt_BR
dc.language.isopt_BRpt_BR
dc.publisherSociedade Brasileira de Automática (SBA) - https://www.sba.org.br/; Galoá Science - https://galoa.com.br/ - https://cba2020.galoa.com.br/pt_BR
dc.subjectPath planningpt_BR
dc.subjectCollision avoidancept_BR
dc.subjectReinforcement learningpt_BR
dc.subjectRobotic manipulatorpt_BR
dc.subjectTrajectory generationpt_BR
dc.titlePath Planning Collision Avoidance using Reinforcement Learningpt_BR
dc.typeArtigo de Eventopt_BR
dc.title.enPath Planning Collision Avoidance using Reinforcement Learningpt_BR
Aparece nas coleções:DEEL - Trabalhos apresentados em eventos

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