A General Purpose Configurable Controller for Indoors and Outdoors GPS-Denied Navigation for Multirotor Unmanned Aerial Vehicles

This research on odometry based GPS-denied navigation on multirotor Unmanned Aerial Vehicles is focused among the interactions between the odometry sensors and the navigation controller. More precisely, we present a controller architecture that allows to specify a speed specified flight envelope where the quality of the odometry measurements is guaranteed. The controller utilizes a simple point mass kinematic model, described by a set of configurable parameters, to generate a complying speed plan. For experimental testing, we have used down-facing camera optical-flow as odometry measurement. This work is a continuation of prior research to outdoors environments using an AR Drone 2.0 vehicle, as it provides reliable optical flow on a wide range of flying conditions and floor textures. Our experiments show that the architecture is realiable for outdoors flight on altitudes lower than 9 m. A prior version of our code was utilized to compete in the International Micro Air Vehicle Conference and Flight Competition IMAV 2012. The code will be released as an open-source ROS stack hosted on GitHub.

A computational model of the anterior intraparietal area

The monkey anterior intraparietal area (AIP) encodes visual information about three-dimensional object shape that is used to shape the hand for grasping. In robotics a similar role has been played by modules that fit point cloud data to the superquadric family of shapes and its various extensions. We developed a model of shape tuning in AIP based on cosine tuning to superquadric parameters. However, the model did not fit the data well, and we also found that it was difficult to accurately reproduce these parameters using neural networks with the appropriate inputs (modelled on the caudal intraparietal area, CIP). The latter difficulty was related to the fact that there are large discontinuities in the superquadric parameters between very similar shapes. To address these limitations we adopted an alternative shape parameterization based on an Isomap nonlinear dimension reduction. The Isomap was built using gradients and curvatures of object surface depth. This alternative parameterization was low-dimensional (like superquadrics), but data-driven (similar to an alternative clustering approach that is also sometimes used in robotics) and lacked large discontinuities. Isomaps with 16 or more dimensions reproduced the AIP data fairly well. Moreover, we found that the Isomap parameters could be approximated from CIP-like input much more accurately than the superquadric parameters. We conclude that Isomaps, or perhaps alternative dimension reductions of CIP signals, provide a promising model of AIP tuning. We have now started to integrate our model with a robot hand, to explore the efficacy of Isomap shape reductions in grasp planning. Future work will consider dynamics of spike responses and integration with related visual and motor area models.

Non-invasive user monitoring in daily tasks for cognitive rehabilitation

El uso de técnicas para la monitorización del movimiento humano generalmente permite a los investigadores analizar la cinemática y especialmente las capacidades motoras en aquellas actividades de la vida cotidiana que persiguen un objetivo concreto como pueden ser la preparación de bebidas y comida, e incluso en tareas de aseo. Adicionalmente, la evaluación del movimiento y el comportamiento humanos en el campo de la rehabilitación cognitiva es esencial para profundizar en las dificultades que algunas personas encuentran en la ejecución de actividades diarias después de accidentes cerebro-vasculares. Estas dificultades están principalmente asociadas a la realización de pasos secuenciales y al reconocimiento del uso de herramientas y objetos. La interpretación de los datos sobre la actitud de este tipo de pacientes para reconocer y determinar el nivel de éxito en la ejecución de las acciones, y para ampliar el conocimiento en las enfermedades cerebrales, sus consecuencias y severidad, depende totalmente de los dispositivos usados para la captura de esos datos y de la calidad de los mismos. Más aún, existe una necesidad real de mejorar las técnicas actuales de rehabilitación cognitiva contribuyendo al diseño de sistemas automáticos para crear una especie de terapeuta virtual que asegure una vida más independiente de estos pacientes y reduzca la carga de trabajo de los terapeutas. Con este objetivo, el uso de sensores y dispositivos para obtener datos en tiempo real de la ejecución y estado de la tarea de rehabilitación es esencial para también contribuir al diseño y entrenamiento de futuros algoritmos que pudieran reconocer errores automáticamente para informar al paciente acerca de ellos mediante distintos tipos de pistas como pueden ser imágenes, mensajes auditivos o incluso videos. La tecnología y soluciones existentes en este campo no ofrecen una manera totalmente robusta y efectiva para obtener datos en tiempo real, por un lado, porque pueden influir en el movimiento del propio paciente en caso de las plataformas basadas en el uso de marcadores que necesitan sensores pegados en la piel; y por otro lado, debido a la complejidad o alto coste de implantación lo que hace difícil pensar en la idea de instalar un sistema en el hospital o incluso en la casa del paciente. Esta tesis presenta la investigación realizada en el campo de la monitorización del movimiento de pacientes para proporcionar un paso adelante en términos de detección, seguimiento y reconocimiento del comportamiento de manos, gestos y cara mediante una manera no invasiva la cual puede mejorar la técnicas actuales de rehabilitación cognitiva para la adquisición en tiempo real de datos sobre el comportamiento del paciente y la ejecución de la tarea. Para entender la importancia del marco de esta tesis, inicialmente se presenta un resumen de las principales enfermedades cognitivas y se introducen las consecuencias que tienen en la ejecución de tareas de la vida diaria. Más aún, se investiga sobre las metodologías actuales de rehabilitación cognitiva. Teniendo en cuenta que las manos son la principal parte del cuerpo para la ejecución de tareas manuales de la vida cotidiana, también se resumen las tecnologías existentes para la captura de movimiento de manos. Una de las principales contribuciones de esta tesis está relacionada con el diseño y evaluación de una solución no invasiva para detectar y seguir las manos durante la ejecución de tareas manuales de la vida cotidiana que a su vez involucran la manipulación de objetos. Esta solución la cual no necesita marcadores adicionales y está basada en una cámara de profundidad de bajo coste, es robusta, precisa y fácil de instalar. Otra contribución presentada se centra en el reconocimiento de gestos para detectar el agarre de objetos basado en un sensor infrarrojo de última generación, y también complementado con una cámara de profundidad. Esta nueva técnica, y también no invasiva, sincroniza ambos sensores para seguir objetos específicos además de reconocer eventos concretos relacionados con tareas de aseo. Más aún, se realiza una evaluación preliminar del reconocimiento de expresiones faciales para analizar si es adecuado para el reconocimiento del estado de ánimo durante la tarea. Por su parte, todos los componentes y algoritmos desarrollados son integrados en un prototipo simple para ser usado como plataforma de monitorización. Se realiza una evaluación técnica del funcionamiento de cada dispositivo para analizar si es adecuada para adquirir datos en tiempo real durante la ejecución de tareas cotidianas reales. Finalmente, se estudia la interacción con pacientes reales para obtener información del nivel de usabilidad del prototipo. Dicha información es esencial y útil para considerar una rehabilitación cognitiva basada en la idea de instalación del sistema en la propia casa del paciente al igual que en el hospital correspondiente. ABSTRACT The use of human motion monitoring techniques usually let researchers to analyse kinematics, especially in motor strategies for goal-oriented activities of daily living, such as the preparation of drinks and food, and even grooming tasks. Additionally, the evaluation of human movements and behaviour in the field of cognitive rehabilitation is essential to deep into the difficulties some people find in common activities after stroke. This difficulties are mainly associated with sequence actions and the recognition of tools usage. The interpretation of attitude data of this kind of patients in order to recognize and determine the level of success of the execution of actions, and to broaden the knowledge in brain diseases, consequences and severity, depends totally on the devices used for the capture of that data and the quality of it. Moreover, there is a real need of improving the current cognitive rehabilitation techniques by contributing to the design of automatic systems to create a kind of virtual therapist for the improvement of the independent life of these stroke patients and to reduce the workload of the occupational therapists currently in charge of them. For this purpose, the use of sensors and devices to obtain real time data of the execution and state of the rehabilitation task is essential to also contribute to the design and training of future smart algorithms which may recognise errors to automatically provide multimodal feedback through different types of cues such as still images, auditory messages or even videos. The technology and solutions currently adopted in the field don't offer a totally robust and effective way for obtaining real time data, on the one hand, because they may influence the patient's movement in case of marker-based platforms which need sensors attached to the skin; and on the other hand, because of the complexity or high cost of implementation, which make difficult the idea of installing a system at the hospital or even patient's home. This thesis presents the research done in the field of user monitoring to provide a step forward in terms of detection, tracking and recognition of hand movements, gestures and face via a non-invasive way which could improve current techniques for cognitive rehabilitation for real time data acquisition of patient's behaviour and execution of the task. In order to understand the importance of the scope of the thesis, initially, a summary of the main cognitive diseases that require for rehabilitation and an introduction of the consequences on the execution of daily tasks are presented. Moreover, research is done about the actual methodology to provide cognitive rehabilitation. Considering that the main body members involved in the completion of a handmade daily task are the hands, the current technologies for human hands movements capture are also highlighted. One of the main contributions of this thesis is related to the design and evaluation of a non-invasive approach to detect and track user's hands during the execution of handmade activities of daily living which involve the manipulation of objects. This approach does not need the inclusion of any additional markers. In addition, it is only based on a low-cost depth camera, it is robust, accurate and easy to install. Another contribution presented is focused on the hand gesture recognition for detecting object grasping based on a brand new infrared sensor, and also complemented with a depth camera. This new, and also non-invasive, solution which synchronizes both sensors to track specific tools as well as recognize specific events related to grooming is evaluated. Moreover, a preliminary assessment of the recognition of facial expressions is carried out to analyse if it is adequate for recognizing mood during the execution of task. Meanwhile, all the corresponding hardware and software developed are integrated in a simple prototype with the purpose of being used as a platform for monitoring the execution of the rehabilitation task. Technical evaluation of the performance of each device is carried out in order to analyze its suitability to acquire real time data during the execution of real daily tasks. Finally, a kind of healthcare evaluation is also presented to obtain feedback about the usability of the system proposed paying special attention to the interaction with real users and stroke patients. This feedback is quite useful to consider the idea of a home-based cognitive rehabilitation as well as a possible hospital installation of the prototype.

Emotion transplantation through adaptation in HMM-based speech synthesis

This paper proposes an emotion transplantation method capable of modifying a synthetic speech model through the use of CSMAPLR adaptation in order to incorporate emotional information learned from a different speaker model while maintaining the identity of the original speaker as much as possible. The proposed method relies on learning both emotional and speaker identity information by means of their adaptation function from an average voice model, and combining them into a single cascade transform capable of imbuing the desired emotion into the target speaker. This method is then applied to the task of transplanting four emotions (anger, happiness, sadness and surprise) into 3 male speakers and 3 female speakers and evaluated in a number of perceptual tests. The results of the evaluations show how the perceived naturalness for emotional text significantly favors the use of the proposed transplanted emotional speech synthesis when compared to traditional neutral speech synthesis, evidenced by a big increase in the perceived emotional strength of the synthesized utterances at a slight cost in speech quality. A final evaluation with a robotic laboratory assistant application shows how by using emotional speech we can significantly increase the students’ satisfaction with the dialog system, proving how the proposed emotion transplantation system provides benefits in real applications.

Spectral study and classification of worldwide locations considering several multijunction solar cell technologies

Multi-junction solar cells are widely used in high-concentration photovoltaic systems (HCPV) attaining the highest efficiencies in photovoltaic energy generation. This technology is more dependent on the spectral variations of the impinging Direct Normal Irradiance (DNI) than conventional photovoltaics based on silicon solar cells and consequently demands a deeper knowledge of the solar resource characteristics. This article explores the capabilities of spectral indexes, namely, spectral matching ratios (SMR), to spectrally characterize the annual irradiation reaching a particular location on the Earth and to provide the necessary information for the spectral optimization of a MJ solar cell in that location as a starting point for CPV module spectral tuning. Additionally, the relationship between such indexes and the atmosphere parameters, such as the aerosol optical depth (AOD), precipitable water (PW), and air mass (AM), is discussed using radiative transfer models such as SMARTS to generate the spectrally-resolved DNI. The network of ground-based sun and sky-scanning radiometers AERONET (AErosol RObotic NETwork) is exploited to obtain the atmosphere parameters for a selected bunch of 34 sites worldwide. Finally, the SMR indexes are obtained for every location, and a comparative analysis is carried out for four architectures of triple junction solar cells, covering both lattice match and metamorphic technologies. The differences found among cell technologies are much less significant than among locations.

Modeling and Simulation of Upper Brachial Plexus Injury

This article presents the first musculoskeletal model and simulation of upper plexus brachial injury. From this model is possible to analyse forces and movement ranges in order to develop a robotic exoskeleton to improve rehabilitation. The software that currently exists for musculoskeletal modeling is varied and most have advanced features for proper analysis and study of motion simulations. Whilst more powerful computer packages are usually expensive, there are other free and open source packages available which offer different tools to perform animations and simulations and which obtain forces and moments of inertia. Among them, Musculoskeletal Modeling Software was selected to construct a model of the upper limb, which has 7 degrees of freedom and 10 muscles. These muscles are important for two of the movements simulated in this article that are part of the post-surgery rehabilitation protocol. We performed different movement animations which are made using the inertial measurement unit to capture real data from movements made by a human being. We also performed the simulation of forces produced in elbow flexion-extension and arm abduction-adduction of a healthy subject and one with upper brachial plexus injury in a postoperative state to compare the force that is capable of being produced in both cases.

A Reliable Open-Source System Architecture for the Fast Designing and Prototyping of Autonomous Multi-UAV Systems: Simulation and Experimentation

During the process of design and development of an autonomous Multi-UAV System, two main problems appear. The first one is the difficulty of designing all the modules and behaviors of the aerial multi-robot system. The second one is the difficulty of having an autonomous prototype of the system for the developers that allows to test the performance of each module even in an early stage of the project. These two problems motivate this paper. A multipurpose system architecture for autonomous multi-UAV platforms is presented. This versatile system architecture can be used by the system designers as a template when developing their own systems. The proposed system architecture is general enough to be used in a wide range of applications, as demonstrated in the paper. This system architecture aims to be a reference for all designers. Additionally, to allow for the fast prototyping of autonomous multi-aerial systems, an Open Source framework based on the previously defined system architecture is introduced. It allows developers to have a flight proven multi-aerial system ready to use, so that they can test their algorithms even in an early stage of the project. The implementation of this framework, introduced in the paper with the name of “CVG Quadrotor Swarm”, which has also the advantages of being modular and compatible with different aerial platforms, can be found at https://​github.​com/​Vision4UAV/​cvg_​quadrotor_​swarm with a consistent catalog of available modules. The good performance of this framework is demonstrated in the paper by choosing a basic instance of it and carrying out simulation and experimental tests whose results are summarized and discussed in this paper.

A Vision-based Quadrotor Multi-robot Solution for the Indoor Autonomy Challenge of the 2013 International Micro Air Vehicle Competition

This paper presents a completely autonomous solution to participate in the Indoor Challenge of the 2013 International Micro Air Vehicle Competition (IMAV 2013). Our proposal is a multi-robot system with no centralized coordination whose robotic agents share their position estimates. The capability of each agent to navigate avoiding collisions is a consequence of the resulting emergent behavior. Each agent consists of a ground station running an instance of the proposed architecture that communicates over WiFi with an AR Drone 2.0 quadrotor. Visual markers are employed to sense and map obstacles and to improve the pose estimation based on Inertial Measurement Unit (IMU) and ground optical flow data. Based on our architecture, each robotic agent can navigate avoiding obstacles and other members of the multi-robot system. The solution is demonstrated and the achieved navigation performance is evaluated by means of experimental flights. This work also analyzes the capabilities of the presented solution in simulated flights of the IMAV 2013 Indoor Challenge. The performance of the CVG UPM team was awarded with the First Prize in the Indoor Autonomy Challenge of the IMAV 2013 competition.

Protein quantification from complex protein mixtures using a proteomics methodology with single-cell resolution

We have developed an extremely sensitive technique, termed immuno-detection amplified by T7 RNA polymerase (IDAT) that is capable of monitoring proteins, lipids, and metabolites and their modifications at the single-cell level. A double-stranded oligonucleotide containing the T7 promoter is conjugated to an antibody (Ab), and then T7 RNA polymerase is used to amplify RNA from the double-stranded oligonucleotides coupled to the Ab in the Ab-antigen complex. By using this technique, we are able to detect the p185her2/neu receptor from the crude lysate of T6–17 cells at 10−13 dilution, which is 109-fold more sensitive than the conventional ELISA method. Single-chain Fv fragments or complementarity determining region peptides of the Ab also can be substituted for the Ab in IDAT. In a modified protocol, the oligonucleotide has been coupled to an Ab against a common epitope to create a universal detector species. With the linear amplification ability of T7 RNA polymerase, IDAT represents a significant improvement over immuno-PCR in terms of sensitivity and has the potential to provide a robotic platform for proteomics.

Role of the monkey ventrolateral prefrontal cortex in the integration of contextual information for the selection and understanding of goal-directed actions

Action selection and organization are very complex processes that need to exploit contextual information and the retrieval of previously memorized information, as well as the integration of these different types of data. On the basis of anatomical connection with premotor and parietal areas involved in action goal coding, and on the data about the literature it seems appropriate to suppose that one of the most candidate involved in the selection of neuronal pools for the selection and organization of intentional actions is the prefrontal cortex. We recorded single ventrolateral prefrontal (VLPF) neurons activity while monkeys performed simple and complex manipulative actions aimed at distinct final goals, by employing a modified and more strictly controlled version of the grasp-to-eat(a food pellet)/grasp-to-place(an object) paradigm used in previous studies on parietal (Fogassi et al., 2005) and premotor neurons (Bonini et al., 2010). With this task we have been able both to evaluate the processing and integration of distinct (visual and auditory) contextual sequentially presented information in order to select the forthcoming action to perform and to examine the possible presence of goal-related activity in this portion of cortex. Moreover, we performed an observation task to clarify the possible contribution of VLPF neurons to the understanding of others’ goal-directed actions. Simple Visuo Motor Task (sVMT). We found four main types of neurons: unimodal sensory-driven, motor-related, unimodal sensory-and-motor, and multisensory neurons. We found a substantial number of VLPF neurons showing both a motor-related discharge and a visual presentation response (sensory-and-motor neurons), with remarkable visuo-motor congruence for the preferred target. Interestingly the discharge of multisensory neurons reflected a behavioural decision independently from the sensory modality of the stimulus allowing the monkey to make it: some encoded a decision to act/refraining from acting (the majority), while others specified one among the four behavioural alternatives. Complex Visuo Motor Task (cVMT). The cVMT was similar to the sVMT, but included a further grasping motor act (grasping a lid in order to remove it, before grasping the target) and was run in two modalities: randomized and in blocks. Substantially, motor-related and sensory-and-motor neurons tested in the cVMTrandomized were activated already during the first grasping motor act, but the selectivity for one of the two graspable targets emerged only during the execution of the second grasping. In contrast, when the cVMT was run in block, almost all these neurons not only discharged during the first grasping motor act, but also displayed the same target selectivity showed in correspondence of the hand contact with the target. Observation Task (OT). A great part of the neurons active during the OT showed a firing rate modulation in correspondence with the action performed by the experimenter. Among them, we found neurons significantly activated during the observation of the experimenter’s action (action observation-related neurons) and neurons responding not only to the action observation, but also to the presented cue stimuli (sensory-and-action observation-related neurons. Among the neurons of the first set, almost the half displayed a target selectivity, with a not clear difference between the two presented targets; Concerning to the second neuronal set, sensory-and-action related neurons, we found a low target selectivity and a not strictly congruence between the selectivity exhibited in the visual response and in the action observation.

Método de estimativa de torque da articulação do joelho baseada em EMG

Este trabalho apresenta um método de estimativa de torque do joelho baseado em sinais eletromiográficos (EMG) durante terapia de reabilitação robótica. Os EMGs, adquiridos de cinco músculos envolvidos no movimento de flexão e extensão do joelho, são processados para encontrar as ativações musculares. Em seguida, mediante um modelo simples de contração muscular, são calculadas as forças e, usando a geometria da articulação, o torque do joelho. As funções de ativação e contração musculares possuem parâmetros limitados que devem ser calibrados para cada usuário, sendo o ajuste feito mediante a minimização do erro entre o torque estimado e o torque medido na articulação usando a dinâmica inversa. São comparados dois métodos iterativos para funções não-lineares como técnicas de otimização restrita para a calibração dos parâmetros: Gradiente Descendente e Quasi-Newton. O processamento de sinais, calibração de parâmetros e cálculo de torque estimado foram desenvolvidos no software MATLAB®; o cálculo de torque medido foi feito no software OpenSim com sua ferramenta de dinâmica inversa.

Simultaneous optical and X-ray observations of flares and rotational modulation on the RS CVn binary HR 1099 (V711 Tau) from the MUSICOS 1998 campaign

We present simultaneous and continuous observations of the Hα, Hβ, He I D_3, Na I D_1,D_2 doublet and the Ca II H&K lines for the RS CVn system HR 1099. The spectroscopic observations were obtained during the MUSICOS 1998 campaign involving several observatories and instruments, both echelle and long-slit spectrographs. During this campaign, HR 1099 was observed almost continuously for more than 8 orbits of 2^d.8. Two large optical flares were observed, both showing an increase in the emission of Hα, Ca II H K, Hβ and He I D_3 and a strong filling-in of the Na I D_1, D_2 doublet. Contemporary photometric observations were carried out with the robotic telescopes APT-80 of Catania and Phoenix-25 of Fairborn Observatories. Maps of the distribution of the spotted regions on the photosphere of the binary components were derived using the Maximum Entropy and Tikhonov photometric regularization criteria. Rotational modulation was observed in Hα and He I D_3 in anti-correlation with the photometric light curves. Both flares occurred at the same binary phase (0.85), suggesting that these events took place in the same active region. Simultaneous X-ray observations, performed by ASM on board RXTE, show several flare-like events, some of which correlate well with the observed optical flares. Rotational modulation in the X-ray light curve has been detected with minimum flux when the less active G5 V star was in front. A possible periodicity in the X-ray flare-like events was also found.

Análise de grandezas cinemáticas e dinâmicas inerentes à hemiparesia através da descoberta de conhecimento em bases de dados

Em virtude de uma elevada expectativa de vida mundial, faz-se crescente a probabilidade de ocorrer acidentes naturais e traumas físicos no cotidiano, o que ocasiona um aumento na demanda por reabilitação. A terapia física, sob o paradigma da reabilitação robótica com serious games, oferece maior motivação e engajamento do paciente ao tratamento, cujo emprego foi recomendado pela American Heart Association (AHA), apontando a mais alta avaliação (Level A) para pacientes internados e ambulatoriais. No entanto, o potencial de análise dos dados coletados pelos dispositivos robóticos envolvidos é pouco explorado, deixando de extrair informações que podem ser de grande valia para os tratamentos. O foco deste trabalho consiste na aplicação de técnicas para descoberta de conhecimento, classificando o desempenho de pacientes diagnosticados com hemiparesia crônica. Os pacientes foram inseridos em um ambiente de reabilitação robótica, fazendo uso do InMotion ARM, um dispositivo robótico para reabilitação de membros superiores e coleta dos dados de desempenho. Foi aplicado sobre os dados um roteiro para descoberta de conhecimento em bases de dados, desempenhando pré-processamento, transformação (extração de características) e então a mineração de dados a partir de algoritmos de aprendizado de máquina. A estratégia do presente trabalho culminou em uma classificação de padrões com a capacidade de distinguir lados hemiparéticos sob uma precisão de 94%, havendo oito atributos alimentando a entrada do mecanismo obtido. Interpretando esta coleção de atributos, foi observado que dados de força são mais significativos, os quais abrangem metade da composição de uma amostra.

Developing Emotional Security Among Children Who Have Been Adopted

This study investigated the development of emotional security among 6-10 year old children who have been adopted by exposing them to an experimental condition during which they could engage with either a live dog or a robotic dog. The live dog was a certified therapy dog; the robotic dog was a FurReal® toy marketed by Hasbro as "Biscuit." Utilizing a mixed-method embedded experimental design, the experimental condition was intentionally structured to promote engagement between the participant and the dog or robot. 43 children who had been adopted from the child welfare system were randomly assigned to one of two groups. One group was exposed to a therapy dog (n=22), while another was exposed to the social robotic dog (n=21). The development of emotional security was targeted for measurement in this study using the "Reading the Mind in the Eyes Test," a test of social understanding that has been linked in the literature to oxytocin- a hormone premised to be a marker of the development of emotional security. Physiological anxiety was also measured as an indicator of emotional security using the Revised Child Manifest Anxiety Scale-2 (RCMAS-2). Both measures were administered before and after exposure to the experimental condition. A linear mixed-effect regression analysis showed that for boys only, there was a significant effect of engagement with either companion on social understanding (p<.01). Social understanding decreased as engagement increased. A second model indicated that for boys only, their history of animal cruelty had a significant effect on physiological anxiety (p<.05). If boys had an animal cruelty history, their anxiety was reduced after the exposure to either the dog or robot. Interpretations of the findings suggest that there are differences among children who have been adopted and have a history of animal cruelty that differentially influences their development of emotional security. Social work interventions designed for practice with children who have been adopted will need to assess the presence of these variations and develop appropriate treatment protocols.

Método de desvio de obstáculos aplicado em veículo autônomo.

A operação de veículos autônomos necessita de meios para evitar colisões quando obstáculos não conhecidos previamente são interpostos em sua trajetória. Algoritmos para executar o desvio e sensores apropriados para a detecção destes obstáculos são essenciais para a operação destes veículos. Esta dissertação apresenta estudos sobre quatro algoritmos de desvio de obstáculos e tecnologia de três tipos de sensores aplicáveis à operação de veículos autônomos. Após os estudos teóricos, um dos algoritmos foi testado para a comprovação da aplicabilidade ao veículo de teste. A etapa experimental foi a realização de um programa, escrito em linguagem de programação Java, que aplicou o algoritmo Inseto 2 para o desvio de obstáculos em uma plataforma robótica (Robodeck) com o uso de sensores ultrassônicos embarcados na referida plataforma. Os experimentos foram conduzidos em ambiente fechado (indoor), bidimensional e horizontal (plano), fazendo o Robodeck executar uma trajetória. Para os testes, obstáculos foram colocados para simular situações variadas e avaliar a eficácia do algoritmo nestas configurações de caminho. O algoritmo executou o desvio dos obstáculos com sucesso e, quando havia solução para a trajetória, ela foi encontrada. Quando não havia solução, o algoritmo detectou esta situação e parou o veículo.