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@Article{2,
  Title                    = {{Compensaci{\'{o}}n de los Efectos Generados en la Imagen por el Control de Navegaci{\'{o}}n del Robot Aibo ERS 7}},
  Author                   = {Aguilar, Wilbert and Angulo, Cecilio},
  Journal                  = {Memorias del VII Congreso de Ciencia y Tecnolog{\'{i}}a ESPE 2012},
  Year                     = {2012},
  Number                   = {JUNE},
  Pages                    = {165--170},

  Doi                      = {10.13140/2.1.3438.2089},
  File                     = {:C$\backslash$:/Users/UPS/Desktop/mobile{\_}robot/3{\_}Compensacion{\_}y{\_}Aprendizaje{\_}de{\_}Efectos{\_}Ge.pdf:pdf},
  ISBN                     = {9788461573981},
  ISSN                     = {1390-4663},
  Keywords                 = {(),como objetivo dise{\~{n}}ar una,de im{\'{a}}genes,el presente trabajo tiene,estimaci{\'{o}}n del error,geometr{\'{i}}a,im{\'{a}}genes,matching,reconocimiento de objetos,reconstrucci{\'{o}}n de,transformaciones,visi{\'{o}}n},
  Owner                    = {UPS},
  Timestamp                = {2016.12.27}
}

@Article{3,
  Title                    = {{Compensaci{\'{o}}n y Aprendizaje de Efectos Generados en la Imagen durante el Desplazamiento de un Robot}},
  Author                   = {Aguilar, Wilbert and Angulo, Cecilio},
  Journal                  = {X Simposio CEA Ingenier{\'{i}}a de Control 1,2 Marzo, 2012},
  Year                     = {2012},
  Pages                    = {165--170},

  Doi                      = {10.13140/2.1.3438.2089},
  File                     = {:C$\backslash$:/Users/UPS/Desktop/mobile{\_}robot/3{\_}Compensacion{\_}y{\_}Aprendizaje{\_}de{\_}Efectos{\_}Ge.pdf:pdf},
  ISBN                     = {9788461573981},
  ISSN                     = {1390-4663},
  Keywords                 = {(),como objetivo dise{\~{n}}ar una,de im{\'{a}}genes,el presente trabajo tiene,estimaci{\'{o}}n del error,geometr{\'{i}}a,im{\'{a}}genes,matching,reconocimiento de objetos,reconstrucci{\'{o}}n de,transformaciones,visi{\'{o}}n},
  Owner                    = {UPS},
  Timestamp                = {2016.12.27}
}

@Article{7,
  Title                    = {{3D Environment Mapping Using the Kinect V2 and Path Planning Based on RRT Algorithms}},
  Author                   = {Aguilar, Wilbert and Morales, Stephanie},
  Journal                  = {Electronics},
  Year                     = {2016},
  Number                   = {4},
  Pages                    = {70},
  Volume                   = {5},

  Abstract                 = {This paper describes a 3D path planning system that is able to provide a solution trajectory for the automatic control of a robot. The proposed system uses a point cloud obtained from the robot workspace,with a Kinect V2 sensor to identify the interest regions and the obstacles of the environment. Our proposal includes a collision-free path planner based on the Rapidly-exploring Random Trees variant (RRT*),for a safe and optimal navigation of robots in 3D spaces. Results on RGB-D segmentation and recognition,point cloud processing,and comparisons between different RRT* algorithms,are presented.},
  Doi                      = {10.3390/electronics5040070},
  File                     = {:C$\backslash$:/Users/UPS/Desktop/mobile{\_}robot/7{\_}3D Environment Mapping Using the Kinect.pdf:pdf},
  ISSN                     = {2079-9292},
  Keywords                 = {3d modeling,computational geometry,mobile robotics,path planning,point cloud registration,rgb-d,rrt,segmentation},
  Owner                    = {UPS},
  Timestamp                = {2016.12.27}
}

@Article{8,
  Title                    = {{Estabilizaci{\'{o}}n de v{\'{i}}deo en micro veh{\'{i}}culos a{\'{e}}reos y su aplicaci{\'{o}}n en la detecci{\'{o}}n de caras}},
  Author                   = {Aguilar, Wilbert G and Angulo, Cecilio},
  Year                     = {2014},
  Pages                    = {155--160},

  File                     = {:C$\backslash$:/Users/UPS/Desktop/mobile{\_}robot/8{\_}Estabilizaci{\'{o}}n de v{\'{i}}deo en micro veh{\'{i}}culos a{\'{e}}reos.pdf:pdf},
  Keywords                 = {control,detecci{\'{o}}n,estabilizaci{\'{o}}n de video,filtro,intenci{\'{o}}n de,micro veh{\'{i}}culos a{\'{e}}reos,movimiento},
  Owner                    = {UPS},
  Timestamp                = {2016.12.27}
}

@Article{1,
  Title                    = {{Vision-based intelligent vehicles: State of the art and perspectives}},
  Author                   = {Bertozzi, Massimo and Broggi, Alberto and Fascioli, Alessandra},
  Journal                  = {Robotics and Autonomous Systems},
  Year                     = {2000},
  Number                   = {1},
  Pages                    = {1--16},
  Volume                   = {32},

  Abstract                 = {Recently, a large emphasis has been devoted to Automatic Vehicle Guidance since the automation of driving tasks carries a large number of benefits, such as the optimization of the use of transport infrastructures, the improvement of mobility, the minimization of risks, travel time, and energy consumption. This paper surveys the most common approaches to the challenging task of Autonomous Road Following reviewing the most promising experimental solutions and prototypes developed worldwide using AI techniques to perceive the environmental situation by means of artificial vision. The most interesting results and trends in this field as well as the perspectives on the evolution of intelligent vehicles in the next decades are also sketched out.},
  Doi                      = {10.1016/S0921-8890(99)00125-6},
  File                     = {:C$\backslash$:/Users/UPS/Desktop/mobile{\_}robot/1{\_}Vision-based intelligent vehicles State of the art and perspectives.pdf:pdf},
  ISSN                     = {09218890},
  Keywords                 = {automatic vehicle guidance,intelligent transportation systems,intelligent vehicles,its,machine vision},
  Owner                    = {UPS},
  Timestamp                = {2016.12.27}
}

@Article{5,
  Title                    = {{Autonomous driving goes downtown}},
  Author                   = {Franke, Uwe and Gavrila, Dariu and G{\"{o}}rzig, Steffen and Lindner, Frank and Paetzold, Frank and W{\"{o}}hler, Christian},
  Journal                  = {IEEE Intelligent Systems and Their Applications},
  Year                     = {1998},
  Number                   = {6},
  Pages                    = {40--48},
  Volume                   = {13},

  Abstract                 = {Most computer-vision systems for vehicle guidance are for highway scenarios. Developing autonomous or driver-assistance systems for complex urban traffic poses new algorithmic and system-architecture challenges. To address these issues, the authors introduce their intelligent Stop{\&}Go system and discuss appropriate algorithms and approaches for vision-module control},
  Doi                      = {10.1109/5254.736001},
  File                     = {:C$\backslash$:/Users/UPS/Desktop/mobile{\_}robot/5{\_}Autonomous driving goes downtown.pdf:pdf},
  ISBN                     = {1094-7167 VO - 13},
  ISSN                     = {10947167},
  Owner                    = {UPS},
  Timestamp                = {2016.12.27}
}

@Article{6,
  Title                    = {{Fast stereo based object detection for stop{\&}go traffic}},
  Author                   = {Franke, U. and Kutzbach, I.},
  Journal                  = {IEEE Intelligent Vehicles Symposium},
  Year                     = {1996},
  Pages                    = {339--344},

  Abstract                 = {This paper presents a new fast binocular stereo approach for the detection and tracking of objects, in particular for stop{\&}go traffic. The proposed scheme is based on a local feature extraction and detects dominant objects by means of a Hough transform like disparity grouping. It is able to handle not only vehicles, but also other objects such as pedestrians. In addition, it allows to determine the camera orientation relative to the road and to distinguish between road surface},
  Doi                      = {10.1109/IVS.1996.566403},
  File                     = {:C$\backslash$:/Users/UPS/Desktop/mobile{\_}robot/6{\_}Fast stereo based object detection for stop{\&}go traffic.pdf:pdf},
  ISBN                     = {0-7803-3652-6},
  Owner                    = {UPS},
  Timestamp                = {2016.12.27}
}

@Article{9,
  Title                    = {{Vision-based pedestrian detection: the PROTECTOR system}},
  Author                   = {Gavrila, D.M. and Giebel, J. and Munder, S.},
  Journal                  = {IEEE Intelligent Vehicles Symposium, 2004},
  Year                     = {2004},
  Pages                    = {13--18},

  Abstract                 = { This paper presents the results of the first large-scale field tests on vision-based pedestrian protection from a moving vehicle. Our PROTECTOR system combines pedestrian detection, trajectory estimation, risk assessment and driver warning. The paper pursues a "system approach" related to the detection component. An optimization scheme models the system as a succession of individual modules and finds a good overall parameter setting by combining individual ROCs using a convex-hull technique. On the experimental side, we present a methodology for the validation of the pedestrian detection performance in an actual vehicle setting. We hope this test methodology to contribute towards the establishment of benchmark testing, enabling this application to mature. We validate the PROTECTOR system using the proposed methodology and present interesting quantitative results based on tens of thousands of images from hours of driving. Although results are promising, more research is needed before such systems can be placed at the hands of ordinary vehicle drivers.},
  Doi                      = {10.1109/IVS.2004.1336348},
  File                     = {:C$\backslash$:/Users/UPS/Desktop/mobile{\_}robot/9{\_}Vision based pedestrian detection the PROTECTOR system.pdf:pdf},
  ISBN                     = {0-7803-8310-9},
  ISSN                     = {0780383109},
  Owner                    = {UPS},
  Timestamp                = {2016.12.27}
}

@Article{4,
  Title                    = {{Are we ready for Autonomous Driving? The $\backslash$textsc{\{}KITTI{\}} Vision Benchmark Suite}},
  Author                   = {Geiger, Andreas and Lenz, Philip and Urtasun, Raquel},
  Journal                  = {Computer Vision and Pattern Recognition},
  Year                     = {2012},
  Pages                    = {3354--3361},

  File                     = {:C$\backslash$:/Users/UPS/Desktop/mobile{\_}robot/4{\_}Are we ready for autonomous driving.pdf:pdf},
  ISBN                     = {9781467312288},
  Owner                    = {UPS},
  Timestamp                = {2016.12.27}
}

@Article{10,
  Title                    = {{Pedestrian detection for driving assistance systems: single-frame classification and system level performance}},
  Author                   = {Shashua, a. and Gdalyahu, Y. and Hayun, G.},
  Journal                  = {IEEE Intelligent Vehicles Symposium, 2004},
  Year                     = {2004},
  Pages                    = {1--6},

  Abstract                 = {We describe the functional and architectural breakdown of a monocular pedestrian detection system. We describe in detail our approach for single-frame classification based on a novel scheme of breaking down the class variability by repeatedly training a set of relatively simple classifiers on clusters of the training set. Single-frame classification performance results and system level performance figures for daytime conditions are presented with a discussion about the remaining gap to meet a daytime normal weather condition production system.},
  Doi                      = {10.1109/IVS.2004.1336346},
  File                     = {:C$\backslash$:/Users/UPS/Desktop/mobile{\_}robot/10{\_}Pedestrian detection for driving assistance systems.pdf:pdf},
  ISBN                     = {0-7803-8310-9},
  Owner                    = {UPS},
  Timestamp                = {2016.12.27}
}

