https://repositorio.cetys.mx/handle/60000/254
Campo DC | Valor | Lengua/Idioma |
---|---|---|
dc.contributor.author | Orozco Rosas, Ulises | - |
dc.contributor.other | Picos, Kenia | es_ES |
dc.contributor.other | Díaz Ramírez, Víctor H. | es_ES |
dc.date.accessioned | 2020-01-20T20:54:09Z | - |
dc.date.available | 2020-01-20T20:54:09Z | - |
dc.date.issued | 2017-08-26 | - |
dc.identifier.uri | doi: 10.1117/12.2273596 | - |
dc.description.abstract | A visual approach in environment recognition for robot navigation is proposed. This work includes a template matching filtering technique to detect obstacles and feasible paths using a single camera to sense a cluttered environment. In this problem statement, a robot can move from the start to the goal by choosing a single path between multiple possible ways. In order to generate an efficient and safe path for mobile robot navigation, the proposal employs a pseudo-bacterial potential field algorithm to derive optimal potential field functions using evolutionary computation. Simulation results are evaluated in synthetic and real scenes in terms of accuracy of environment recognition and efficiency of path planning computation. | es_ES |
dc.language.iso | en_US | es_ES |
dc.rights | Atribución-NoComercial-CompartirIgual 2.5 México | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-sa/2.5/mx/ | * |
dc.subject | Environment recognition | es_ES |
dc.subject | Robot vision | es_ES |
dc.subject | Template matching filters | es_ES |
dc.subject | Path planning | es_ES |
dc.subject | Pseudo-bacterial potential field | es_ES |
dc.title | Visual environment recognition for robot path planning using template matched filters | es_ES |
dc.type | Presentation | es_ES |
dc.contributor.aditional | Montiel, Oscar | - |
dc.contributor.aditional | Sepúlveda, Roberto | - |
dc.identifier.doi | 10.1117/12.2273596 | - |
dc.subject.sede | Campus Tijuana | es_ES |
Aparece en las colecciones: | Ponencias |
Fichero | Descripción | Tamaño | Formato | |
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[conf_2017]_VisEnvRec (1).pdf | 1.01 MB | Adobe PDF | Visualizar/Abrir |
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