Objekto atpažinimas ir pozicijos nustatymas gali būti pritaikomas daugeliui pramonėje egzistuojančių uždavinių. Šio darbo pagrindinis tikslas yra sukurti mašininės regos sistemą, kuria būtų galima greitai ir tiksliai rasti objekto poziciją pagal pasirinktą objekto modelį. Šiame darbe gilinamasi į GPU veikimo principus ir privalumus apdorojant vaizdus GLSL programavimo kalba. Apžvelgiami praktikoje taikomų metodų, skirtų objekto pozicijai nustatyti, veikimo principai, jų privalumai ir trūkumai. Taip pat šiame darbe aprašomas suformuotas ir įgyvendintas realaus laiko metodas, naudojantis GPU teikiama sparta atlikti vartotojo pasirinkto modelio paiešką. Pabaigoje pateikiami pasiekti įgyvendinto metodo spartos rodikliai, privalumai ir trūkumai. Darbą sudaro: įvadas, mašininėje regoje pasitaikančių problemų tyrinėjimas, objekto paieškos metodų apžvalga, darbo su grafinėmis vaizdo plokštėmis privalumai ir trūkumai, objekto paieškos su grafine vaizdo plokšte metodas, pasiekti rezultatai, išvados ir literatūros sąrašas. Darbo apimtis – 53 p. teksto be priedų, 30 pav., 2 lent., 26 literatūros šaltiniai. / Object recognition and parameter detection could be used in many areas from electronics to food industry. One of the most important problems in laser industry is to transform laser work trajectories based on constant object model. In the real life applications model could be rotated or translated due to the fact that object must be put in laser work area. The translation and rotation of object must be found to fit user defined constant model. There are many methods for object parameters detection, but image processing tasks require a lot of computing power. Recent research on image processing with graphics processing units - GPU, shows huge performance results compared with central processing units – CPU. The purpose of this work is to find out the main fundamentals for fast and accurate object parameter detection in machine vision systems. In this work it is focused on object parameter detection with GPU. Moreover, the analysis and comparison of different object parameters detection methods are proposed. Object parameter detection system was implemented with C++ and GLSL shading language, thus the system could be adapted to different computer hardware and operating systems. Work size – 53 p. text, 30 illustrations, 2 tables, 26 bibliographic sources.

Mémoire numérisé par la Division de la gestion de documents et des archives de l'Université de Montréal

The objective of this work is to make a step towards an artificial system with human-like visual intelligence capabilities. We consider the following three visual recognition problems. First, we show how to identify the same object or scene instance in a large database of images despite significant changes in appearance due to viewpoint, illumination but also aging, seasonal changes, or depiction style. Second, we consider recognition of object classes such as "chairs" or "windows" (as opposed to a specific instance of a chair or a window). We investigate how to name object classes present in the image, identify their locations as well as predict their approximate 3D model and fine-grained style ("Is this a bar stool or a folding chair?"; "Is this a bay window or a French window?"). In particular, we investigate different levels of supervision for this task starting from just observing images without any supervision to having millions of labelled images or a set of full 3D models. Finally, we consider recognition of people and their actions in unconstrained videos such as TV or feature length films. In detail, we investigate how to identify individual people in the video using their faces ("Who is this?") as well as recognize what they do ("Is this person walking or sitting?").

Purpose: Schizophrenia is a progressive degenerative illness that has been causally linked to mitochondrial dysfunction, oxidative stress and a pro-inflammatory state. Social isolation rearing (SIR) in rats models the neurodevelopmental aspects of schizophrenia. The antioxidant and glutamate modulator, N-acetyl cysteine (NAC), has demonstrated therapeutic potential in schizophrenia as adjunctive treatment, although this has not been tested in the SIR model. The purpose of this study was to assess whether SIR induces changes in mitochondrial function (adenosine triphosphate (ATP)), pro- vs. anti-inflammatory cytokine balance, tryptophan metabolism, a disturbance in cortico-striatal monoamines and related metabolites, and associated alterations in behaviors akin to schizophrenia, viz. social interaction, object recognition memory and prepulse inhibition (PPI). Moreover, I evaluated whether these bio-behavioral alterations could be reversed with sub-chronic clozapine, or NAC, and whether NAC may bolster the response to clozapine treatment. Methods: The objectives of the study were pursued through separately conducted studies. Male Sprague-Dawley (SD) rats (10 rats/group) were used in this study (Ethics number: NWU-0035-08-S5). Rats were randomly allocated to either social rearing or SIR for 8 weeks receiving either no treatment, vehicle, NAC (150 mg/kg/day), clozapine (5 mg/kg/day) or a combination of clozapine + NAC (CLZ + NAC) during the last 11 or 14 days of social rearing or SIR. After the 8 weeks, rats were tested for social interactive behaviors, object recognition memory and prepulse inhibition (PPI). Peripheral tryptophan metabolites (determined by liquid chromatography-tandem mass spectrometry (LC-MS/MS)) and pro- and anti-inflammatory cytokines (IL-4, IL-6, TNF-α, IFN-γ) (enzyme-linked immunosorbent assay (ELISA)) were determined. Cortico-striatal ATP (bioluminescence assay) and monoamines (high performance liquid chromatography (HPLC)) were also determined. Results: SIR-induced significant deficits in social interactive behaviours, object recognition memory and PPI, associated with increased peripheral kynurenine, quinolinic acid (QA), and pro-inflammatory cytokines, as well as a decrease in kynurenic acid (KYNA), neuroprotective ratio and anti-inflammatory cytokines. I also observed an increase in striatal, but reduced frontal cortical ATP, dopamine, serotonin as well as their metabolites and noradrenaline’s metabolite, with noradrenaline increased in both brain regions in SIR rats. A separate dose-response study of NAC (50, 150, 250 mg/kg/day) found 150 mg/kg to be the most appropriate dose for the NAC and CLZ + NAC studies. Clozapine, NAC as well as CLZ + NAC reversed all these changes, with NAC being less effective than CLZ alone. CLZ + NAC was found to be more effective than clozapine alone in reversing certain bio-behavioral alterations induced by SIR. In addition NAC alone dose dependently reversed most of the SIR induced alterations. Conclusion: SIR induces behavioral alterations, a pro-inflammatory state, mitochondrial dysfunction and cortico-striatal monoamine alterations, closely resembling evidence in schizophrenia. Importantly, all these bio-behavioral alterations were reversed with clozapine, NAC and CLZ + NAC treatment. However, CLZ + NAC was more effective than clozapine alone in reversing some bio-behavioral alterations, supporting the therapeutic application of NAC as adjunctive treatment in schizophrenia. In addition, NAC dose dependently reversed SIR-induced cortico-striatal serotonin, noradrenaline and metabolites, emphasizing NAC’s potential use in other anxiety and stress- related disorders. / Thesis (PhD (Pharmacology))--North-West University, Potchefstroom Campus, 2013

Purpose: Schizophrenia is a progressive degenerative illness that has been causally linked to mitochondrial dysfunction, oxidative stress and a pro-inflammatory state. Social isolation rearing (SIR) in rats models the neurodevelopmental aspects of schizophrenia. The antioxidant and glutamate modulator, N-acetyl cysteine (NAC), has demonstrated therapeutic potential in schizophrenia as adjunctive treatment, although this has not been tested in the SIR model. The purpose of this study was to assess whether SIR induces changes in mitochondrial function (adenosine triphosphate (ATP)), pro- vs. anti-inflammatory cytokine balance, tryptophan metabolism, a disturbance in cortico-striatal monoamines and related metabolites, and associated alterations in behaviors akin to schizophrenia, viz. social interaction, object recognition memory and prepulse inhibition (PPI). Moreover, I evaluated whether these bio-behavioral alterations could be reversed with sub-chronic clozapine, or NAC, and whether NAC may bolster the response to clozapine treatment. Methods: The objectives of the study were pursued through separately conducted studies. Male Sprague-Dawley (SD) rats (10 rats/group) were used in this study (Ethics number: NWU-0035-08-S5). Rats were randomly allocated to either social rearing or SIR for 8 weeks receiving either no treatment, vehicle, NAC (150 mg/kg/day), clozapine (5 mg/kg/day) or a combination of clozapine + NAC (CLZ + NAC) during the last 11 or 14 days of social rearing or SIR. After the 8 weeks, rats were tested for social interactive behaviors, object recognition memory and prepulse inhibition (PPI). Peripheral tryptophan metabolites (determined by liquid chromatography-tandem mass spectrometry (LC-MS/MS)) and pro- and anti-inflammatory cytokines (IL-4, IL-6, TNF-α, IFN-γ) (enzyme-linked immunosorbent assay (ELISA)) were determined. Cortico-striatal ATP (bioluminescence assay) and monoamines (high performance liquid chromatography (HPLC)) were also determined. Results: SIR-induced significant deficits in social interactive behaviours, object recognition memory and PPI, associated with increased peripheral kynurenine, quinolinic acid (QA), and pro-inflammatory cytokines, as well as a decrease in kynurenic acid (KYNA), neuroprotective ratio and anti-inflammatory cytokines. I also observed an increase in striatal, but reduced frontal cortical ATP, dopamine, serotonin as well as their metabolites and noradrenaline’s metabolite, with noradrenaline increased in both brain regions in SIR rats. A separate dose-response study of NAC (50, 150, 250 mg/kg/day) found 150 mg/kg to be the most appropriate dose for the NAC and CLZ + NAC studies. Clozapine, NAC as well as CLZ + NAC reversed all these changes, with NAC being less effective than CLZ alone. CLZ + NAC was found to be more effective than clozapine alone in reversing certain bio-behavioral alterations induced by SIR. In addition NAC alone dose dependently reversed most of the SIR induced alterations. Conclusion: SIR induces behavioral alterations, a pro-inflammatory state, mitochondrial dysfunction and cortico-striatal monoamine alterations, closely resembling evidence in schizophrenia. Importantly, all these bio-behavioral alterations were reversed with clozapine, NAC and CLZ + NAC treatment. However, CLZ + NAC was more effective than clozapine alone in reversing some bio-behavioral alterations, supporting the therapeutic application of NAC as adjunctive treatment in schizophrenia. In addition, NAC dose dependently reversed SIR-induced cortico-striatal serotonin, noradrenaline and metabolites, emphasizing NAC’s potential use in other anxiety and stress- related disorders. / Thesis (PhD (Pharmacology))--North-West University, Potchefstroom Campus, 2013

As robotic systems move from well-controlled settings to increasingly unstructured environments, they are required to operate in highly dynamic and cluttered scenarios. Finding an object, estimating its pose, and tracking its pose over time within such scenarios are challenging problems. Although various approaches have been developed to tackle these problems, the scope of objects addressed and the robustness of solutions remain limited. In this thesis, we target a robust object perception using visual sensory information, which spans from the traditional monocular camera to the more recently emerged RGB-D sensor, in unstructured environments. Toward this goal, we address four critical challenges to robust 6-DOF object pose estimation and tracking that current state-of-the-art approaches have, as yet, failed to solve. The first challenge is how to increase the scope of objects by allowing visual perception to handle both textured and textureless objects. A large number of 3D object models are widely available in online object model databases, and these object models provide significant prior information including geometric shapes and photometric appearances. We note that using both geometric and photometric attributes available from these models enables us to handle both textured and textureless objects. This thesis presents our efforts to broaden the spectrum of objects to be handled by combining geometric and photometric features. The second challenge is how to dependably estimate and track the pose of an object despite the clutter in backgrounds. Difficulties in object perception rise with the degree of clutter. Background clutter is likely to lead to false measurements, and false measurements tend to result in inaccurate pose estimates. To tackle significant clutter in backgrounds, we present two multiple pose hypotheses frameworks: a particle filtering framework for tracking and a voting framework for pose estimation. Handling of object discontinuities during tracking, such as severe occlusions, disappearances, and blurring, presents another important challenge. In an ideal scenario, a tracked object is visible throughout the entirety of tracking. However, when an object happens to be occluded by other objects or disappears due to the motions of the object or the camera, difficulties ensue. Because the continuous tracking of an object is critical to robotic manipulation, we propose to devise a method to measure tracking quality and to re-initialize tracking as necessary. The final challenge we address is performing these tasks within real-time constraints. Our particle filtering and voting frameworks, while time-consuming, are composed of repetitive, simple and independent computations. Inspired by that observation, we propose to run massively parallelized frameworks on a GPU for those robotic perception tasks which must operate within strict time constraints.

The ability to learn is essential for robots to function and perform services within a dynamic human environment. Robot programming by demonstration facilitates learning through a human teacher without the need to develop new code for each task that the robot performs. In order for learning to be generalizable, the robot needs to be able to grasp the underlying structure of the task being learned. This requires appropriate knowledge abstraction and representation. The goal of this thesis is to develop a learning by imitation system that abstracts knowledge of human demonstrations of a task and represents the abstracted knowledge in a hierarchical framework. The learning by imitation system is capable of performing both action and object recognition based on video stream data at the lower level of the hierarchy, while the sequence of actions and object states observed is reconstructed at the higher level of the hierarchy in order to form a coherent representation of the task. Furthermore, error recovery capabilities are included in the learning by imitation system to improve robustness to unexpected situations during task execution. The first part of the thesis focuses on motion learning to allow the robot to both recognize the actions for task representation at the higher level of the hierarchy and to perform the actions to imitate the task. In order to efficiently learn actions, the actions are segmented into meaningful atomic units called motion primitives. These motion primitives are then modeled using dynamic movement primitives (DMPs), a dynamical system model that can robustly generate motion trajectories to arbitrary goal positions while maintaining the overall shape of the demonstrated motion trajectory. The DMPs also contain weight parameters that are reflective of the shape of the motion trajectory. These weight parameters are clustered using affinity propagation (AP), an efficient exemplar clustering algorithm, in order to determine groups of similar motion primitives and thus, performing motion recognition. The approach of DMPs combined with APs was experimentally verified on two separate motion data sets for its ability to recognize and generate motion primitives. The second part of the thesis outlines how the task representation is created and used for imitating observed tasks. This includes object and object state recognition using simple computer vision techniques as well as the automatic construction of a Petri net (PN) model to describe an observed task. Tasks are composed of a sequence of actions that have specific pre-conditions, i.e. object states required before the action can be performed, and post-conditions, i.e. object states that result from the action. The PNs inherently encode pre-conditions and post-conditions of a particular event, i.e. action, and can model tasks as a coherent sequence of actions and object states. In addition, PNs are very flexible in modeling a variety of tasks including tasks that involve both sequential and parallel components. The automatic PN creation process has been tested on both a sequential two block stacking task and a three block stacking task involving both sequential and parallel components. The PN provides a meaningful representation of the observed tasks that can be used by a robot to imitate the tasks. Lastly, error recovery capabilities are added to the learning by imitation system in order to allow the robot to readjust the sequence of actions needed during task execution. The error recovery component is able to deal with two types of errors: unexpected, but known situations and unexpected, unknown situations. In the case of unexpected, but known situations, the learning system is able to search through the PN to identify the known situation and the actions needed to complete the task. This ability is useful not only for error recovery from known situations, but also for human robot collaboration, where the human unexpectedly helps to complete part of the task. In the case of situations that are both unexpected and unknown, the robot will prompt the human demonstrator to teach how to recover from the error to a known state. By observing the error recovery procedure and automatically extending the PN with the error recovery information, the situation encountered becomes part of the known situations and the robot is able to autonomously recover from the error in the future. This error recovery approach was tested successfully on errors encountered during the three block stacking task.

Video editing and object recognition are two significant fields in computer vi- sion: the first has remarkably assisted digital production and post-production tasks of a digital video footage; the second is considered fundamental to image classification or image based search in large databases (e.g. the web). In this thesis, we address two problems, namely we present a novel formulation that tackles video editing tasks and we develop a mechanism that allows to generate more robust descriptors for objects in an image. Concerning the first problem, this thesis proposes two variational models to perform temporally coherent video editing. These models are applied to change an object’s (rigid or non-rigid) texture throughout a given video sequence. One model is based on propagating color information from a given frame (or be- tween two given frames) along the motion trajectories of the video; while the other is based on propagating gradient domain information. The models we present in this thesis require minimal user intervention and they automatically accommodate for illumination changes in the scene. Concerning the second problem, this thesis addresses the problem of affine invariance in object recognition. We introduce a way to generate geometric affine invariant quantities that are used in the construction of feature descrip- tors. We show that when these quantities are used they do indeed achieve a more robust recognition than the state of the art descriptors. i / La edición de vídeo y el reconocimiento de objetos son dos áreas fundamentales en el campo de la visión por computador: la primera es de gran utilidad en los procesos de producción y post-producción digital de vídeo; la segunda es esencial para la clasificación o búsqueda de imágenes en grandes bases de datos (por ejemplo, en la web). En esta tesis se acometen ambos problemas, en concreto, se presenta una nueva formulación que aborda las tareas de edición de vídeo y se desarrolla un mecanismo que permite generar descriptores más robustos para los objetos de la imagen. Con respecto al primer problema, en esta tesis se proponen dos modelos variacionales para llevar a cabo la edición de vídeo de forma coherente en el tiempo. Estos modelos se aplican para cambiar la textura de un objeto (rígido o no) a lo largo de una secuencia de vídeo dada. Uno de los modelos está basado en la propagación de la información de color desde un determinado cuadro de la secuencia de vídeo (o entre dos cuadros dados) a lo largo de las trayectorias de movimiento del vídeo. El otro modelo está basado en la propagación de la información en el dominio del gradiente. Ambos modelos requieren una intervención mínima por parte del usuario y se ajustan de manera automática a los cambios de iluminación de la escena. Con respecto al segundo problema, esta tesis aborda el problema de la invariancia afín en el reconocimiento de objetos. Se introduce un nuevo método para generar cantidades geométricas afines que se utilizan en la generación de descriptores de características. También se demuestra que el uso de dichas cantidades proporciona mayor robustez al reconocimiento que los descriptores existentes actualmente en el estado del arte.

Conselho Nacional de Desenvolvimento Científico e Tecnológico / Alzheimer s disease (AD) is biochemically characterized by the occurrence of extracellular deposits of amyloid beta peptide (Aβ) and intracellular deposits of the hyperphosphorylated tau protein, which are causally related to the pathological hallmarks senile plaques and neurofibrillary tangles. Monoamine oxidase B (MAO-B) activity, an enzyme involved in the oxidation of biogenic monoamines, is particularly high around the senile plaques and increased in AD patients in middle to late clinical stages of the disease. Selegiline, a selective and irreversible MAO-B inhibitor, improves learning and memory in AD patients. Notwithstanding, its mechanism of action is still not completely known. The current study aimed to investigate whether selegiline improves the Aβ25-35 induced cognitive deficit in the object recognition task in mice. In addition, we investigated whether selegiline alters MAO-B and MAO-A activities in the hippocampus, perirhinal and remaining cerebral cortices of Aβ25-35-injected mice. Acute (1 and 10 mg/kg, p.o., immediately post-training) and subchronic (10 mg/kg, p.o., seven days after Aβ25-35 injection and immediately post-training) administration of selegiline reversed the cognitive impairment induced by Aβ25-35 (3 nmol, i.c.v.). Acute administration of selegiline (1 mg/kg, p.o.) in combination with Aβ25-35 (3 nmol) decreased MAO-B activity in the perirhinal and remaining cerebral cortices. Acute administration of selegiline (10 mg/kg, p.o.) decreased MAO-B activity in hippocampus, perirhinal and remaining cerebral cortices, regardless of Aβ25-35 or Aβ35-25 treatment. MAO-A activity was not altered by selegiline or Aβ25-35. In summary, the current findings further support a role for MAO-B in the cognitive deficits observed in AD. / A doença de Alzheimer (DA) é bioquimicamente caracterizada por depósitos extracelulares de peptídeo beta amiloide (Aβ) e de proteína tau hiperfosforilada, que são causalmente relacionadas com as características patológicas, placas neuríticas e emaranhados neurofibrilares. A atividade da monoamina oxidase B (MAO-B), uma enzima envolvida na oxidação de monoaminas biogênicas, é particularmente elevada ao redor das placas senis e aumenta nos pacientes com DA em estágios clínicos de moderado a grave. A selegilina, um inibidor seletivo e irreversível da MAO-B, é relatada por melhorar a memória e o aprendizado em pacientes com DA. Porém, seu mecanismo de ação ainda não é completamente conhecido. O presente estudo teve como objetivo investigar se a selegilina melhora o déficit cognitivo induzido por Aβ25-35. na tarefa de reconhecimento de objetos em camundongos. Além disso, investigou-se a atividade da MAO-A e da MAO-B no hipocampo, no córtex cerebral e no córtex perirrinal de camundongos injetados com Aβ25-35 e com selegilina. Administração aguda (1 e 10 mg/kg, p.o., imediatamente pós-treino) e subcrônica (10 mg/kg, p.o., por sete dias depois da injeção do Aβ25-35 e imediatamente pós-treino) de selegilina preveniu o prejuízo da memória induzido pelo Aβ25-35 (3 nmol, icv). A administração aguda de selegilina (1 mg/kg, p.o.) em combinação com Aβ25-35 (3 nmol) diminuiu a atividade da MAO-B no córtex perirrinal e córtex cerebral. A administração aguda de selegilina (10 mg/kg, p.o.) diminuiu a atividade da MAO-B no hipocampo, no córtex cerebral e no córtex perirrinal independentemente da presença de Aβ25-35. A atividade da MAO-A não foi alterada pelo tratamento com selegilina ou Aβ25-35 em nenhuma das estruturas estudadas. Em resumo, os dados atuais suportam um papel adicional para a MAO-B no déficit cognitivo observado na DA.

In the industrial area, robots are an important part of the technological resources available to perform manipulation tasks in manufacturing, assembly, the transportation of dangerous waste, and a variety of applications. Specialized systems of computer vision have entered the market to solve problems that other technologies have been unable to address. This document analyzes a stereo vision system that is used to provide the center of mass of an object in three dimensions. This kind of application is mounted using two or more cameras that are aligned along the same axis and give the possibility to measure the depth of a point in the space. The stereoscopic system described, measures the position of an object using a combination between the 2D recognition, which implies the calculus of the coordinates of the center of mass and using moments, and the disparity that is found comparing two images: one of the right and one of the left. This converts the system into a 3D reality viewfinder, emulating the human eyes, which are capable of distinguishing depth with good precision.The proposed stereo vision system is integrated into a 5 degree of freedom pneumatic robot, which can be programmed using the GRAFCET method by means of commercial software. The cameras are mounted in the lateral plane of the robot to ensure that all the pieces in the robot's work area can be observed.For the implementation, an algorithm is developed for recognition and position measurement using open sources in C++. This ensures that the system can remain as open as possible once it is integrated with the robot. The validation of the work is accomplished by taking samples of the objects to be manipulated and generating robot's trajectories to see if the object can be manipulated by its end effector or not. The results show that is possible to manipulate pieces in a visually crowded space with acceptable precision. However, the precision reached does not allow the robot to perform tasks that require higher accuracy as the one is needed in manufacturing assembly process of little pieces or in welding applications. / En el área industrial los robots forman parte importante del recurso tecnológico disponible para tareas de manipulación en manufactura, ensamble, manejo de residuos peligrosos y aplicaciones varias. Los sistemas de visión computacional se han ingresado al mercado como soluciones a problemas que otros tipos de sensores y métodos no han podido solucionar. El presente trabajo analiza un sistema de visión estereoscópico aplicado a un robot. Este arreglo permite la medición de coordenadas del centro de un objeto en las tres dimensiones, de modo que, le da al robot la posibilidad de trabajar en el espacio y no solo en un plano. El sistema estereoscópico consiste en el uso de dos o más cámaras alineadas en alguno de sus ejes, mediante las cuales, es posible calcular la profundidad a la que se encuentran los objetos. En el presente, se mide la posición de un objeto haciendo una combinación entre el reconocimiento 2D y la medición de las coordenadas y de su centro calculadas usando momentos. En el sistema estereoscópico, se añade la medición de la última coordenada mediante el cálculo de la disparidad encontrada entre las imágenes de las cámaras inalámbricas izquierda y derecha, que convierte al sistema en un visor 3D de la realidad, emulando los ojos humanos capaces de distinguir profundidades con cierta precisión. El sistema de visión computacional propuesto es integrado a un robot neumático de 5 grados de libertad el cual puede ser programado desde la metodología GRAFCET mediante software de uso comercial. Las cámaras del sistema de visión están montadas en el plano lateral del robot de modo tal, que es posible visualizar las piezas que quedan dentro de su volumen de trabajo. En la implementación, se desarrolla un algoritmo de reconocimiento y medición de posición, haciendo uso de software libre en lenguaje C++. De modo que, en la integración con el robot, el sistema pueda ser lo más abierto posible. La validación del trabajo se logra tomando muestras de los objetos a ser manipulados y generando trayectorias para el robot, a fin de visualizar si la pieza pudo ser captada por su garra neumática o no. Los resultados muestran que es posible lograr la manipulación de piezas en un ambiente visualmente cargado y con una precisión aceptable. Sin embargo, se observa que la precisión no permite que el sistema pueda ser usado en aplicaciones donde se requiere precisión al nivel de los procesos de ensamblado de piezas pequeñas o de soldadura.