@InProceedings{monteiro2002obtenccao,
  author      = {Monteiro, Sildomar T. and Ribeiro, Carlos H.C.},
  title       = {Obten{\c{c}}{\~a}o de mapas cognitivos para o rob\^{o} m{\'o}vel Magellan Pro},
  booktitle   = {XIV Congresso Brasileiro de Autom{\'a}tica (CBA)},
  year        = {2002},
  pages       = {1543-1548},
  url         = {https://github.com/sildomar/sildomar.github.io/raw/master/files/Monteiro_CBA_2002.pdf},
  abstract    = {This paper presents the implementation of a method for the efficient learning of cognitive maps of indoor environments on a Magellan Pro mobile robot. The obtained world model is constituted by partitions of variable size representing perceptually homogeneous regions of the environment. The method used is a combination of metric and topological paradigms and produces a map of rectangular partitions of low complexity, based on the assumption that obstacles are parallel or perpendicular to each other. A neural network is used to interpret sonar readings. Experimental results show that the method allows learning of a reliable map of the environment for the Magellan Pro robot, using solely sonar readings.},
  address     = {Natal, Brazil},
  journal     = {Anais do XII CBA},
  keywords    = {Autonomous mobile robots, map learning, neural networks, occupancy grid, robotics, topological graph},
  url_citedby = {https://scholar.google.com/scholar?cites=9767360953387033821},
}

{"_id":"cLgPK6eq9sujXY9ew","bibbaseid":"monteiro-ribeiro-obtenodemapascognitivosparaorobmvelmagellanpro-2002","author_short":["Monteiro, S. T.","Ribeiro, C. H."],"bibdata":{"bibtype":"inproceedings","type":"inproceedings","author":[{"propositions":[],"lastnames":["Monteiro"],"firstnames":["Sildomar","T."],"suffixes":[]},{"propositions":[],"lastnames":["Ribeiro"],"firstnames":["Carlos","H.C."],"suffixes":[]}],"title":"Obtenção de mapas cognitivos para o robô móvel Magellan Pro","booktitle":"XIV Congresso Brasileiro de Automática (CBA)","year":"2002","pages":"1543-1548","url":"https://github.com/sildomar/sildomar.github.io/raw/master/files/Monteiro_CBA_2002.pdf","abstract":"This paper presents the implementation of a method for the efficient learning of cognitive maps of indoor environments on a Magellan Pro mobile robot. The obtained world model is constituted by partitions of variable size representing perceptually homogeneous regions of the environment. The method used is a combination of metric and topological paradigms and produces a map of rectangular partitions of low complexity, based on the assumption that obstacles are parallel or perpendicular to each other. A neural network is used to interpret sonar readings. Experimental results show that the method allows learning of a reliable map of the environment for the Magellan Pro robot, using solely sonar readings.","address":"Natal, Brazil","journal":"Anais do XII CBA","keywords":"Autonomous mobile robots, map learning, neural networks, occupancy grid, robotics, topological graph","url_citedby":"https://scholar.google.com/scholar?cites=9767360953387033821","bibtex":"@InProceedings{monteiro2002obtenccao,\n author = {Monteiro, Sildomar T. and Ribeiro, Carlos H.C.},\n title = {Obten{\\c{c}}{\\~a}o de mapas cognitivos para o rob\\^{o} m{\\'o}vel Magellan Pro},\n booktitle = {XIV Congresso Brasileiro de Autom{\\'a}tica (CBA)},\n year = {2002},\n pages = {1543-1548},\n url = {https://github.com/sildomar/sildomar.github.io/raw/master/files/Monteiro_CBA_2002.pdf},\n abstract = {This paper presents the implementation of a method for the efficient learning of cognitive maps of indoor environments on a Magellan Pro mobile robot. The obtained world model is constituted by partitions of variable size representing perceptually homogeneous regions of the environment. The method used is a combination of metric and topological paradigms and produces a map of rectangular partitions of low complexity, based on the assumption that obstacles are parallel or perpendicular to each other. A neural network is used to interpret sonar readings. Experimental results show that the method allows learning of a reliable map of the environment for the Magellan Pro robot, using solely sonar readings.},\n address = {Natal, Brazil},\n journal = {Anais do XII CBA},\n keywords = {Autonomous mobile robots, map learning, neural networks, occupancy grid, robotics, topological graph},\n url_citedby = {https://scholar.google.com/scholar?cites=9767360953387033821},\n}\n\n","author_short":["Monteiro, S. T.","Ribeiro, C. H."],"key":"monteiro2002obtenccao","id":"monteiro2002obtenccao","bibbaseid":"monteiro-ribeiro-obtenodemapascognitivosparaorobmvelmagellanpro-2002","role":"author","urls":{"Paper":"https://github.com/sildomar/sildomar.github.io/raw/master/files/Monteiro_CBA_2002.pdf"," citedby":"https://scholar.google.com/scholar?cites=9767360953387033821"},"keyword":["Autonomous mobile robots","map learning","neural networks","occupancy grid","robotics","topological graph"],"metadata":{"authorlinks":{}}},"bibtype":"inproceedings","biburl":"https://raw.githubusercontent.com/sildomar/sildomar.github.io/master/files/mypapers.bib","dataSources":["9pKPXHaxkKcJ5Habx"],"keywords":["autonomous mobile robots","map learning","neural networks","occupancy grid","robotics","topological graph"],"search_terms":["obten","mapas","cognitivos","para","rob","vel","magellan","pro","monteiro","ribeiro"],"title":"Obtenção de mapas cognitivos para o robô móvel Magellan Pro","year":2002}