Mapeamento de ambientes estruturados com extração de informações geométricas através de dados sensoriais

The objective of this thesis is proposes a method for a mobile robot to build a hybrid map of an indoor, semi-structured environment. The topological part of this map deals with spatial relationships among rooms and corridors. It is a topology-based map, where the edges of the graph are rooms or corridors, and each link between two distinct edges represents a door. The metric part of the map consists in a set of parameters. These parameters describe a geometric figure which adapts to the free space of the local environment. This figure is calculated by a set of points which sample the boundaries of the local free space. These points are obtained with range sensors and with knowledge about the robot s pose. A method based on generalized Hough transform is applied to this set of points in order to obtain the geomtric figure. The building of the hybrid map is an incremental procedure. It is accomplished while the robot explores the environment. Each room is associated with a metric local map and, consequently, with an edge of the topo-logical map. During the mapping procedure, the robot may use recent metric information of the environment to improve its global or relative pose

RoboEduc: uma metodologia de aprendizado com robótica educacional

In this work, we propose a methodology for teaching robotics in elementary schools, based on the socio-historical Vygotsky theory. This methodology in conjunction with the Lego Mindstoms kit (R) and an educational software (an interface for control and programming of prototypes) are part of an educational robotics system named RoboEduc. For the practical development of this work, we have used the action-research strategy, being realized robotics activities with participation of children with age between 8 and 10 years, students of the elementary school level of Municipal School Ascendino de Almeida. This school is located at the city zone of Pitimbu, at the periphery of Natal, in Rio Grande do Norte state. The activities have focused on understanding the construction of robotic prototypes, their programming and control. At constructing prototypes, children develop zone of proximal development (ZPDs) that are learning spaces that, when well used, allow the construction not only of scientific concepts by the individuals but also of abilities and capabilities that are important for the social and cultural interactiond of each one and of the group. With the development of these practical workshops, it was possible to analyse the use of the Robot as the mediator element of the teaching-learning process and the contributions that the use of robotics may bring to teaching since elementary levels

Aprendizado por Reforço com Valores deInfluência em Sistemas Multi-Agente

We propose a new paradigm for collective learning in multi-agent systems (MAS) as a solution to the problem in which several agents acting over the same environment must learn how to perform tasks, simultaneously, based on feedbacks given by each one of the other agents. We introduce the proposed paradigm in the form of a reinforcement learning algorithm, nominating it as reinforcement learning with influence values. While learning by rewards, each agent evaluates the relation between the current state and/or action executed at this state (actual believe) together with the reward obtained after all agents that are interacting perform their actions. The reward is a result of the interference of others. The agent considers the opinions of all its colleagues in order to attempt to change the values of its states and/or actions. The idea is that the system, as a whole, must reach an equilibrium, where all agents get satisfied with the obtained results. This means that the values of the state/actions pairs match the reward obtained by each agent. This dynamical way of setting the values for states and/or actions makes this new reinforcement learning paradigm the first to include, naturally, the fact that the presence of other agents in the environment turns it a dynamical model. As a direct result, we implicitly include the internal state, the actions and the rewards obtained by all the other agents in the internal state of each agent. This makes our proposal the first complete solution to the conceptual problem that rises when applying reinforcement learning in multi-agent systems, which is caused by the difference existent between the environment and agent models. With basis on the proposed model, we create the IVQ-learning algorithm that is exhaustive tested in repetitive games with two, three and four agents and in stochastic games that need cooperation and in games that need collaboration. This algorithm shows to be a good option for obtaining solutions that guarantee convergence to the Nash optimum equilibrium in cooperative problems. Experiments performed clear shows that the proposed paradigm is theoretical and experimentally superior to the traditional approaches. Yet, with the creation of this new paradigm the set of reinforcement learning applications in MAS grows up. That is, besides the possibility of applying the algorithm in traditional learning problems in MAS, as for example coordination of tasks in multi-robot systems, it is possible to apply reinforcement learning in problems that are essentially collaborative

Localização e mapeamento simultâneos de ambientes planos usando visão monocular e representação híbrida do ambiente

The goal of this work is to propose a SLAM (Simultaneous Localization and Mapping) solution based on Extended Kalman Filter (EKF) in order to make possible a robot navigates along the environment using information from odometry and pre-existing lines on the floor. Initially, a segmentation step is necessary to classify parts of the image in floor or non floor . Then the image processing identifies floor lines and the parameters of these lines are mapped to world using a homography matrix. Finally, the identified lines are used in SLAM as landmarks in order to build a feature map. In parallel, using the corrected robot pose, the uncertainty about the pose and also the part non floor of the image, it is possible to build an occupancy grid map and generate a metric map with the obstacle s description. A greater autonomy for the robot is attained by using the two types of obtained map (the metric map and the features map). Thus, it is possible to run path planning tasks in parallel with localization and mapping. Practical results are presented to validate the proposal

Um sistema de visão para navegação robusta de uma plataforma robótica semi-autônoma

Large efforts have been maden by the scientific community on tasks involving locomotion of mobile robots. To execute this kind of task, we must develop to the robot the ability of navigation through the environment in a safe way, that is, without collisions with the objects. In order to perform this, it is necessary to implement strategies that makes possible to detect obstacles. In this work, we deal with this problem by proposing a system that is able to collect sensory information and to estimate the possibility for obstacles to occur in the mobile robot path. Stereo cameras positioned in parallel to each other in a structure coupled to the robot are employed as the main sensory device, making possible the generation of a disparity map. Code optimizations and a strategy for data reduction and abstraction are applied to the images, resulting in a substantial gain in the execution time. This makes possible to the high level decision processes to execute obstacle deviation in real time. This system can be employed in situations where the robot is remotely operated, as well as in situations where it depends only on itself to generate trajectories (the autonomous case)

Mapeamento robótico 2,5-D com representação em grade de ocupação-elevação

This work introduces a new method for environment mapping with three-dimensional information from visual information for robotic accurate navigation. Many approaches of 3D mapping using occupancy grid typically requires high computacional effort to both build and store the map. We introduce an 2.5-D occupancy-elevation grid mapping, which is a discrete mapping approach, where each cell stores the occupancy probability, the height of the terrain at current place in the environment and the variance of this height. This 2.5-dimensional representation allows that a mobile robot to know whether a place in the environment is occupied by an obstacle and the height of this obstacle, thus, it can decide if is possible to traverse the obstacle. Sensorial informations necessary to construct the map is provided by a stereo vision system, which has been modeled with a robust probabilistic approach, considering the noise present in the stereo processing. The resulting maps favors the execution of tasks like decision making in the autonomous navigation, exploration, localization and path planning. Experiments carried out with a real mobile robots demonstrates that this proposed approach yields useful maps for robot autonomous navigation

Mapeamento com Sonar Usando Grade de Ocupação baseado em Modelagem Probabilística

In this work, we propose a probabilistic mapping method with the mapped environment represented through a modified occupancy grid. The main idea of the proposed method is to allow a mobile robot to construct in a systematic and incremental way the geometry of the underlying space, obtaining at the end a complete environment map. As a consequence, the robot can move in the environment in a safe way, based on a confidence value of data obtained from its perceptive system. The map is represented in a coherent way, according to its sensory data, being these noisy or not, that comes from exterior and proprioceptive sensors of the robot. Characteristic noise incorporated in the data from these sensors are treated by probabilistic modeling in such a way that their effects can be visible in the final result of the mapping process. The results of performed experiments indicate the viability of the methodology and its applicability in the area of autonomous mobile robotics, thus being an contribution to the field

Plataforma Robótica de Baixíssimo Custo para Robótica Educacional

Robots are present each time more on several areas of our society, however they are still considered expensive equipments that are restricted to few people. This work con- sists on the development of control techniques and architectures that make possible the construction and programming of low cost robots with low programming and building complexity. One key aspect of the proposed architecture is the use of audio interfaces to control actuators and read sensors, thus allowing the usage of any device that can produce sounds as a control unit of a robot. The work also includes the development of web ba- sed programming environments that allow the usage of computers or mobile phones as control units of the robot, which can be remotely programmed and controlled. The work also includes possible applications of such low cost robotic platform, including mainly its educational usage, which was experimentally validated by teachers and students of seve- ral graduation courses. We also present an analysis of data obtained from interviews done with the students before and after the use of our platform, which confirms its acceptance as a teaching support tool

Um método para determinação da profundidade combinando visão estéreo e autocalibração para aplicação em robótica móvel

This work proposes a method to determine the depth of objects in a scene using a combination between stereo vision and self-calibration techniques. Determining the rel- ative distance between visualized objects and a robot, with a stereo head, it is possible to navigate in unknown environments. Stereo vision techniques supply a depth measure by the combination of two or more images from the same scene. To achieve a depth estimates of the in scene objects a reconstruction of this scene geometry is necessary. For such reconstruction the relationship between the three-dimensional world coordi- nates and the two-dimensional images coordinates is necessary. Through the achievement of the cameras intrinsic parameters it is possible to make this coordinates systems relationship. These parameters can be gotten through geometric camera calibration, which, generally is made by a correlation between image characteristics of a calibration pattern with know dimensions. The cameras self-calibration allows the achievement of their intrinsic parameters without using a known calibration pattern, being possible their calculation and alteration during the displacement of the robot in an unknown environment. In this work a self-calibration method based in the three-dimensional polar coordinates to represent image features is presented. This representation is determined by the relationship between images features and horizontal and vertical opening cameras angles. Using the polar coordinates it is possible to geometrically reconstruct the scene. Through the proposed techniques combination it is possible to calculate a scene objects depth estimate, allowing the robot navigation in an unknown environment

RoboEduc: especificação de um software educacional para ensino da robótica às crianças como uma ferramenta de inclusão digital

Because of social exclusion in Brazil and having as focus the digital inclusion, was started in Federal University of Rio Grande do Norte a project that could talk, at the same time, about concepts of collaborative learning and educational robotics , focused on children digitally excluded. In this context was created a methodology that approaches many subjects as technological elements (e. g. informatics and robotics) and school subjects (e. g. Portuguese, Mathematics, Geography, History), contextualized in everyday situations. We observed educational concepts of collaborative learning and the development of capacities from those students, as group work, logical knowledge and learning ability. This paper proposes an educational software for robotics teaching called RoboEduc, created to be used by children digitally excluded from primary school. Its introduction prioritizes a friendly interface, that makes the concepts of robotics and programming easy and fun to be taught. With this new tool, users without informatics or robotics previous knowledge are able to control a robot, previously set with Lego kits, or even program it to carry some activities out. This paper provides the implementation of the second version of the software. This version presents the control of the robot already used. After were implemented the different levels of programming linked to the many learning levels of the users and their different interfaces and functions. Nowadays, has been implemented the third version, with the improvement of each one of the mentioned stages. In order to validate, prove and test the efficience of the developed methodology to the RoboEduc, were made experiments, through practice of robotics, with children for fourth and fifth grades of primary school at the City School Professor Ascendino de Almeida, in the suburb of Natal (west zone), Rio Grande do Norte. As a preliminary result of the current technology, we verified that the use of robots associated with a well elaborated software can be spread to users that know very little about the subject, without the necessity of previous advanced technology knowledges. Therefore, they showed to be accessible and efficient tools in the process of digital inclusion

Uma abordagem comportamental para inserção de robôs em ambientes culturais

In this work, we propose methodologies and computer tools to insert robots in cultural environments. The basic idea is to have a robot in a real context (a cultural space) that can represent an user connected to the system through Internet (visitor avatar in the real space) and that the robot also have its representation in a Mixed Reality space (robot avatar in the virtual space). In this way, robot and avatar are not simply real and virtual objects. They play a more important role in the scenery, interfering in the process and taking decisions. In order to have this service running, we developed a module composed by a robot, communication tools and ways to provide integration of these with the virtual environment. As welI we implemented a set of behaviors with the purpose of controlling the robot in the real space. We studied available software and hardware tools for the robotics platform used in the experiments, as welI we developed test routines to determine their potentialities. Finally, we studied the behavior-based control model, we planned and implemented alI the necessary behaviors for the robot integration to the real and virtual cultural spaces. Several experiments were conducted, in order to validate the developed methodologies and tools

Multi-resolução com fóvea móvel para redução e abstração de dados em tempo real

We propose a new approach to reduction and abstraction of visual information for robotics vision applications. Basically, we propose to use a multi-resolution representation in combination with a moving fovea for reducing the amount of information from an image. We introduce the mathematical formalization of the moving fovea approach and mapping functions that help to use this model. Two indexes (resolution and cost) are proposed that can be useful to choose the proposed model variables. With this new theoretical approach, it is possible to apply several filters, to calculate disparity and to obtain motion analysis in real time (less than 33ms to process an image pair at a notebook AMD Turion Dual Core 2GHz). As the main result, most of time, the moving fovea allows the robot not to perform physical motion of its robotics devices to keep a possible region of interest visible in both images. We validate the proposed model with experimental results

Localização de robôs móveis autônomos utilizando fusão sensorial de odometria e visão monocular

The development and refinement of techniques that make simultaneous localization and mapping (SLAM) for an autonomous mobile robot and the building of local 3-D maps from a sequence of images, is widely studied in scientific circles. This work presents a monocular visual SLAM technique based on extended Kalman filter, which uses features found in a sequence of images using the SURF descriptor (Speeded Up Robust Features) and determines which features can be used as marks by a technique based on delayed initialization from 3-D straight lines. For this, only the coordinates of the features found in the image and the intrinsic and extrinsic camera parameters are avaliable. Its possible to determine the position of the marks only on the availability of information of depth. Tests have shown that during the route, the mobile robot detects the presence of characteristics in the images and through a proposed technique for delayed initialization of marks, adds new marks to the state vector of the extended Kalman filter (EKF), after estimating the depth of features. With the estimated position of the marks, it was possible to estimate the updated position of the robot at each step, obtaining good results that demonstrate the effectiveness of monocular visual SLAM system proposed in this paper