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Campo DC | Valor | Idioma |
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dc.contributor.author | Batista, Josias Guimarães | - |
dc.contributor.author | Vasconcelos, Felipe José de Sousa | - |
dc.contributor.author | Ramos, Kaio Martins | - |
dc.contributor.author | Souza, Darielson Araújo de | - |
dc.contributor.author | Silva, José Leonardo Nunes da | - |
dc.date.accessioned | 2022-04-18T13:23:00Z | - |
dc.date.available | 2022-04-18T13:23:00Z | - |
dc.date.issued | 2020 | - |
dc.identifier.citation | BATISTA, 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.v2i1.1597 | pt_BR |
dc.identifier.issn | 2525-8311 | - |
dc.identifier.other | DOI: https://doi.org/10.48011/asba.v2i1.1597 | - |
dc.identifier.uri | http://www.repositorio.ufc.br/handle/riufc/65101 | - |
dc.description.abstract | Industrial 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.iso | pt_BR | pt_BR |
dc.publisher | Sociedade Brasileira de Automática (SBA) - https://www.sba.org.br/; Galoá Science - https://galoa.com.br/ - https://cba2020.galoa.com.br/ | pt_BR |
dc.subject | Path planning | pt_BR |
dc.subject | Collision avoidance | pt_BR |
dc.subject | Reinforcement learning | pt_BR |
dc.subject | Robotic manipulator | pt_BR |
dc.subject | Trajectory generation | pt_BR |
dc.title | Path Planning Collision Avoidance using Reinforcement Learning | pt_BR |
dc.type | Artigo de Evento | pt_BR |
dc.title.en | Path Planning Collision Avoidance using Reinforcement Learning | pt_BR |
Aparece nas coleções: | DEEL - Trabalhos apresentados em eventos |
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Arquivo | Descrição | Tamanho | Formato | |
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2020_eve_jgbatista.pdf | 4,54 MB | Adobe PDF | Visualizar/Abrir |
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