Monte Carlo localization on gaussian process occupancy maps for urban environments (2018)
- Authors:
- Autor USP: WOLF, DENIS FERNANDO - ICMC
- Unidade: ICMC
- DOI: 10.1109/TITS.2017.2761774
- Subjects: PROCESSOS GAUSSIANOS; MÉTODO DE MONTE CARLO; ROBÔS; APRENDIZADO COMPUTACIONAL; COMPUTAÇÃO MÓVEL
- Keywords: Vehicle localization; Vehicle localization Gaussian process occupancy map; occupancy grid map; curb detection; road marking detection; Monte Carlo localization
- Language: Inglês
- Imprenta:
- Publisher place: Piscataway, NJ
- Date published: 2018
- Source:
- Título: IEEE Transactions on Intelligent Transportation Systems
- ISSN: 1524-9050
- Volume/Número/Paginação/Ano: v. 19, n. 9, p. 2893-2902, Set. 2018
- Este periódico é de acesso aberto
- Este artigo NÃO é de acesso aberto
-
ABNT
HATA, Alberto Y e RAMOS, Fabio T. e WOLF, Denis Fernando. Monte Carlo localization on gaussian process occupancy maps for urban environments. IEEE Transactions on Intelligent Transportation Systems, v. 19, n. 9, p. 2893-2902, 2018Tradução . . Disponível em: https://doi.org/10.1109/TITS.2017.2761774. Acesso em: 27 fev. 2026. -
APA
Hata, A. Y., Ramos, F. T., & Wolf, D. F. (2018). Monte Carlo localization on gaussian process occupancy maps for urban environments. IEEE Transactions on Intelligent Transportation Systems, 19( 9), 2893-2902. doi:10.1109/TITS.2017.2761774 -
NLM
Hata AY, Ramos FT, Wolf DF. Monte Carlo localization on gaussian process occupancy maps for urban environments [Internet]. IEEE Transactions on Intelligent Transportation Systems. 2018 ; 19( 9): 2893-2902.[citado 2026 fev. 27 ] Available from: https://doi.org/10.1109/TITS.2017.2761774 -
Vancouver
Hata AY, Ramos FT, Wolf DF. Monte Carlo localization on gaussian process occupancy maps for urban environments [Internet]. IEEE Transactions on Intelligent Transportation Systems. 2018 ; 19( 9): 2893-2902.[citado 2026 fev. 27 ] Available from: https://doi.org/10.1109/TITS.2017.2761774 - A road following approach using artificial neural networks combinations
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Informações sobre o DOI: 10.1109/TITS.2017.2761774 (Fonte: oaDOI API)
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