Localização de um robô móvel usando odometria e marcos naturais

Several methods of mobile robot navigation request the mensuration of robot position and orientation in its workspace. In the wheeled mobile robot case, techniques based on odometry allow to determine the robot localization by the integration of incremental displacements of its wheels. However, this technique is subject to errors that accumulate with the distance traveled by the robot, making unfeasible its exclusive use. Other methods are based on the detection of natural or artificial landmarks present in the environment and whose location is known. This technique doesnt generate cumulative errors, but it can request a larger processing time than the methods based on odometry. Thus, many methods make use of both techniques, in such a way that the odometry errors are periodically corrected through mensurations obtained from landmarks. Accordding to this approach, this work proposes a hybrid localization system for wheeled mobile robots in indoor environments based on odometry and natural landmarks. The landmarks are straight lines de.ned by the junctions in environments floor, forming a bi-dimensional grid. The landmark detection from digital images is perfomed through the Hough transform. Heuristics are associated with that transform to allow its application in real time. To reduce the search time of landmarks, we propose to map odometry errors in an area of the captured image that possesses high probability of containing the sought mark

Modelagem linear e identificação do modelo dinâmico de um robô móvel com acionamento diferencial

This work presents a modelling and identification method for a wheeled mobile robot, including the actuator dynamics. Instead of the classic modelling approach, where the robot position coordinates (x,y) are utilized as state variables (resulting in a non linear model), the proposed discrete model is based on the travelled distance increment Delta_l. Thus, the resulting model is linear and time invariant and it can be identified through classical methods such as Recursive Least Mean Squares. This approach has a problem: Delta_l can not be directly measured. In this paper, this problem is solved using an estimate of Delta_l based on a second order polynomial approximation. Experimental data were colected and the proposed method was used to identify the model of a real robot

Localização de robôs móveis em ambientes fechados utilizando câmeras montadas no teto

The localization of mobile robots in indoor environments finds lots of problems such as accumulated errors and the constant changes that occur at these places. A technique called global vision intends to localize robots using images acquired by cameras placed in such a way that covers the place where the robots movement takes place. Localization is obtained by marks put on top of the robot. Algorithms applied to the images search for the mark on top of the robot and by finding the mark they are able to get the position and orientation of the robot. Such techniques used to face some difficulties related with the hardware capacity, fact that limited their execution in real time. However, the technological advances of the last years changed that situation and enabling the development and execution of such algorithms in plain capacity. The proposal specified here intends to develop a mobile robot localization system at indoor environments using a technique called global vision to track the robot and acquire the images, all in real time, intending to improve the robot localization process inside the environment. Being a localization method that takes just actual information in its calculations, the robot localization using images fit into the needs of this kind of place. Besides, it enables more accurate results and in real time, what is exactly the museum application needs.

Planejamento de trajetórias e navegação de robôs móveis

Oil exploration at great depths requires the use of mobile robots to perform various operations such as maintenance, assembly etc. In this context, the trajectory planning and navigation study of these robots is relevant, as the great challenge is to navigate in an environment that is not fully known. The main objective is to develop a navigation algorithm to plan the path of a mobile robot that is in a given position (

Planejamento de trajetórias e navegação de robôs móveis

Oil exploration at great depths requires the use of mobile robots to perform various operations such as maintenance, assembly etc. In this context, the trajectory planning and navigation study of these robots is relevant, as the great challenge is to navigate in an environment that is not fully known. The main objective is to develop a navigation algorithm to plan the path of a mobile robot that is in a given position (

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

Desenvolvimento de um Sistema de Visão Global para uma Frota de Mini-Robôs Móveis

Navigation based on visual feedback for robots, working in a closed environment, can be obtained settling a camera in each robot (local vision system). However, this solution requests a camera and capacity of local processing for each robot. When possible, a global vision system is a cheapest solution for this problem. In this case, one or a little amount of cameras, covering all the workspace, can be shared by the entire team of robots, saving the cost of a great amount of cameras and the associated processing hardware needed in a local vision system. This work presents the implementation and experimental results of a global vision system for mobile mini-robots, using robot soccer as test platform. The proposed vision system consists of a camera, a frame grabber and a computer (PC) for image processing. The PC is responsible for the team motion control, based on the visual feedback, sending commands to the robots through a radio link. In order for the system to be able to unequivocally recognize each robot, each one has a label on its top, consisting of two colored circles. Image processing algorithms were developed for the eficient computation, in real time, of all objects position (robot and ball) and orientation (robot). A great problem found was to label the color, in real time, of each colored point of the image, in time-varying illumination conditions. To overcome this problem, an automatic camera calibration, based on clustering K-means algorithm, was implemented. This method guarantees that similar pixels will be clustered around a unique color class. The obtained experimental results shown that the position and orientation of each robot can be obtained with a precision of few millimeters. The updating of the position and orientation was attained in real time, analyzing 30 frames per second

Evolving Future Internet clean-slate Entity Title Architecture with quality-oriented control-plane extensions

A Internet atual vem sofrendo vários problemas em termos de escalabilidade, desempenho, mobilidade, etc., devido ao vertiginoso incremento no número de usuários e o surgimento de novos serviços com novas demandas, propiciando assim o nascimento da Internet do Futuro. Novas propostas sobre redes orientadas a conteúdo, como a arquitetura Entidade Titulo (ETArch), proveem novos serviços para este tipo de cenários, implementados sobre o paradigma de redes definidas por software. Contudo, o modelo de transporte do ETArch é equivalente ao modelo best-effort da Internet atual, e vem limitando a confiabilidade das suas comunicações. Neste trabalho, ETArch é redesenhado seguindo o paradigma do sobreaprovisionamento de recursos para conseguir uma alocação de recursos avançada integrada com OpenFlow. Como resultado, o framework SMART (Suporte de Sessões Móveis com Alta Demanda de Recursos de Transporte), permite que a rede defina semanticamente os requisitos qualitativos das sessões para assim gerenciar o controle de Qualidade de Serviço visando manter a melhor Qualidade de Experiência possível. A avaliação do planos de dados e de controle teve lugar na plataforma de testes na ilha do projeto OFELIA, mostrando o suporte de aplicações móveis multimídia com alta demanda de recursos de transporte com QoS e QoE garantidos através de um esquema de sinalização restrito em comparação com o ETArch legado