{"id":76,"date":"2017-09-10T05:46:36","date_gmt":"2017-09-10T05:46:36","guid":{"rendered":"https:\/\/ryma.cinvestav.mx\/atorres\/?page_id=76"},"modified":"2017-11-11T17:35:18","modified_gmt":"2017-11-11T17:35:18","slug":"publicaciones","status":"publish","type":"page","link":"https:\/\/ryma.cinvestav.mx\/atorres\/publicaciones\/","title":{"rendered":"Publicaciones"},"content":{"rendered":"

[et_pb_section bb_built=\u00bb1″ fullwidth=\u00bbon\u00bb specialty=\u00bboff\u00bb background_image=\u00bbhttps:\/\/ryma.cinvestav.mx\/atorres\/wp-content\/uploads\/sites\/8\/2017\/09\/IMAGEN-CAMPA\u00d1A1.jpg\u00bb _builder_version=\u00bb3.0.72″ background_color_gradient_start=\u00bbrgba(0,0,0,0.56)\u00bb background_color_gradient_end=\u00bb#ffffff\u00bb background_color_gradient_direction=\u00bb122deg\u00bb background_color_gradient_direction_radial=\u00bbleft\u00bb background_color_gradient_start_position=\u00bb9%\u00bb locked=\u00bbon\u00bb global_module=\u00bb98″][et_pb_fullwidth_header admin_label=\u00bbNombre del Investigador\u00bb global_parent=\u00bb98″ title=\u00bbDRA. LUZ ABRIL TORRES M\u00c9NDEZ\u00bb subhead=\u00bbProfesor Investigador\u00bb background_layout=\u00bbdark\u00bb text_orientation=\u00bbleft\u00bb header_fullscreen=\u00bboff\u00bb header_scroll_down=\u00bboff\u00bb content_orientation=\u00bbcenter\u00bb image_orientation=\u00bbcenter\u00bb title_font=\u00bb|on|||\u00bb subhead_font=\u00bb|on|||\u00bb custom_button_one=\u00bboff\u00bb button_one_letter_spacing=\u00bb0″ button_one_icon_placement=\u00bbright\u00bb button_one_letter_spacing_hover=\u00bb0″ custom_button_two=\u00bboff\u00bb button_two_letter_spacing=\u00bb0″ button_two_icon_placement=\u00bbright\u00bb button_two_letter_spacing_hover=\u00bb0″ subhead_font_size=\u00bb20px\u00bb _builder_version=\u00bb3.0.72″ background_overlay_color=\u00bbrgba(0,0,0,0.3)\u00bb parent_locked=\u00bbon\u00bb \/][et_pb_fullwidth_menu global_parent=\u00bb98″ menu_id=\u00bb6″ background_layout=\u00bblight\u00bb text_orientation=\u00bbleft\u00bb submenu_direction=\u00bbdownwards\u00bb fullwidth_menu=\u00bboff\u00bb active_link_color=\u00bbrgba(131,0,233,0.81)\u00bb menu_font=\u00bb|on|||\u00bb _builder_version=\u00bb3.0.72″ background_color_gradient_start=\u00bb#009f93″ background_color_gradient_end=\u00bbrgba(0,0,0,0.27)\u00bb background_color_gradient_start_position=\u00bb20%\u00bb background_color=\u00bb#d3d3d3″ parent_locked=\u00bbon\u00bb \/][\/et_pb_section][et_pb_section bb_built=\u00bb1″ _builder_version=\u00bb3.0.72″ custom_css_main_element=\u00bbbox-shadow: inset 0px 3px 2px rgba(50, 50, 50, 0.75);\u00bb locked=\u00bboff\u00bb][et_pb_row parent_locked=\u00bboff\u00bb background_position=\u00bbtop_left\u00bb background_repeat=\u00bbrepeat\u00bb background_size=\u00bbinitial\u00bb][et_pb_column type=\u00bb4_4″][et_pb_text _builder_version=\u00bb3.0.72″ background_layout=\u00bblight\u00bb text_orientation=\u00bbleft\u00bb border_style=\u00bbsolid\u00bb parent_locked=\u00bboff\u00bb]<\/p>\n

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PUBLICACIONES<\/strong><\/h2><\/div><\/div>\n

Para ver las publicaciones de todo Rob\u00f3tica y Manufactura Avanzada, ver:\u00a0 Publicaciones RYMA<\/a><\/strong><\/p>\n

<\/a>
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2016<\/h3>

Art\u00edculos de revista<\/h3>

Perez-Alcocer, R. R.; Torres-Mendez, Luz Abril; Olguin-Diaz, Ernesto; Maldonado-Ramirez, Alejandro<\/p>

Vision-based Autonomous Underwater Vehicle Navigation in Poor Visibility Conditions using a Model-free Robust Control Art\u00edculo de revista<\/span> <\/p>

En: <\/span>2016<\/span>.<\/p>

BibTeX<\/a><\/span><\/p>

@article{P\\'{e}rez-Alcocer2016,
\r\ntitle = {Vision-based Autonomous Underwater Vehicle Navigation in Poor Visibility Conditions using a Model-free Robust Control},
\r\nauthor = {Perez-Alcocer, R. R. and Torres-Mendez, Luz Abril and Olguin-Diaz, Ernesto and Maldonado-Ramirez, Alejandro },
\r\nyear  = {2016},
\r\ndate = {2016-06-06},
\r\nkeywords = {},
\r\npubstate = {published},
\r\ntppubtype = {article}
\r\n}
\r\n<\/pre><\/div>
Cerrar<\/a><\/p><\/div><\/div><\/div>
 Maldonado-Ramirez, Alejandro;  Torres-Mendez, Luz Abril<\/p>
Robotic Visual Tracking of Relevant Cues in Underwater Environments with Poor Visibility Conditions<\/a> Art\u00edculo de revista<\/span> <\/p>
En: <\/span>Journal of Sensors, <\/span>vol. 2016, <\/span>2016<\/span>.<\/p>
Resumen<\/a><\/span> | Enlaces<\/a><\/span> | BibTeX<\/a><\/span><\/p>
@article{maldonado2016robotic,
\r\ntitle = {Robotic Visual Tracking of Relevant Cues in Underwater Environments with Poor Visibility Conditions},
\r\nauthor = {Maldonado-Ramirez, Alejandro and Torres-Mendez, Luz Abril},
\r\nurl = {https:\/\/www.hindawi.com\/journals\/js\/2016\/4265042\/},
\r\nyear  = {2016},
\r\ndate = {2016-01-01},
\r\njournal = {Journal of Sensors},
\r\nvolume = {2016},
\r\npublisher = {Hindawi Publishing Corporation},
\r\nabstract = {Using visual sensors for detecting regions of interest in underwater environments is fundamental for many robotic applications. Particularly, for an autonomous exploration task, an underwater vehicle must be guided towards features that are of interest. If the relevant features can be seen from the distance, then smooth control movements of the vehicle are feasible in order to position itself close enough with the final goal of gathering visual quality images. However, it is a challenging task for a robotic system to achieve stable tracking of the same regions since marine environments are unstructured and highly dynamic and usually have poor visibility. In this paper, a framework that robustly detects and tracks regions of interest in real time is presented. We use the chromatic channels of a perceptual uniform color space to detect relevant regions and adapt a visual attention scheme to underwater scenes. For the tracking, we associate with each relevant point superpixel descriptors which are invariant to changes in illumination and shape. The field experiment results have demonstrated that our approach is robust when tested on different visibility conditions and depths in underwater explorations.},
\r\nkeywords = {},
\r\npubstate = {published},
\r\ntppubtype = {article}
\r\n}
\r\n<\/pre><\/div>
Cerrar<\/a><\/p><\/div>
Using visual sensors for detecting regions of interest in underwater environments is fundamental for many robotic applications. Particularly, for an autonomous exploration task, an underwater vehicle must be guided towards features that are of interest. If the relevant features can be seen from the distance, then smooth control movements of the vehicle are feasible in order to position itself close enough with the final goal of gathering visual quality images. However, it is a challenging task for a robotic system to achieve stable tracking of the same regions since marine environments are unstructured and highly dynamic and usually have poor visibility. In this paper, a framework that robustly detects and tracks regions of interest in real time is presented. We use the chromatic channels of a perceptual uniform color space to detect relevant regions and adapt a visual attention scheme to underwater scenes. For the tracking, we associate with each relevant point superpixel descriptors which are invariant to changes in illumination and shape. The field experiment results have demonstrated that our approach is robust when tested on different visibility conditions and depths in underwater explorations.<\/div>
Cerrar<\/a><\/p><\/div>