899 resultados para Humanoid Robots
Resumo:
Este trabalho apresenta o desenvolvimento de um método de coordenação e cooperação para uma frota de mini-robôs móveis. O escopo do desenvolvimento é o futebol de robôs. Trata-se de uma plataforma bem estruturada, dinâmica e desenvolvida no mundo inteiro. O futebol de robôs envolve diversos campos do conhecimento incluindo: visão computacional, teoria de controle, desenvolvimento de circuitos microcontrolados, planejamento cooperativo, entre outros. A título de organização os sistema foi dividido em cinco módulos: robô, visão, localização, planejamento e controle. O foco do trabalho se limita ao módulo de planejamento. Para auxiliar seu desenvolvimento um simulador do sistema foi implementado. O simulador funciona em tempo real e substitui os robôs reais. Dessa forma os outros módulos permanecem praticamente inalterados durante uma simulação ou execução com robôs reais. Para organizar o comportamento dos robôs e produzir a cooperação entre eles foi adotada uma arquitetura hierarquizada: no mais alto nível está a escolha do estilo de jogo do time; logo abaixo decide-se o papel que cada jogador deve assumir; associado ao papel temos uma ação específica e finalmente calcula-se a referência de movimento do robô. O papel de um robô dita o comportamento do robô na dada ocasião. Os papéis são alocados dinamicamente durante o jogo de forma que um mesmo robô pode assumir diferentes papéis no decorrer da partida
Resumo:
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
Resumo:
This paper presents methodology based on Lev Vigotsky`s social interactionist theory through investigative activities, which integrates the teaching of physics to robotics, directed to students of the Physics degree course, seeking to provide further training for future teachers. The method is organized through educational robotics workshops that addresses concepts of physics through the use of low-cost educational robots along with several activities. The methodology has been presented and discussed and put into practice afterwards in workshops so that these future teachers may be able to take robotics to their classroom. Students from the last and penultimate semester of the Physics degree course of the Federal Institute of Education, Science and Technology of Rio Grande do Norte, Caicó campus participated in this project
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We propose an online configurable multiplatform development environment specifically developed for educational robotics applications. The environment, which appears as an extension of RoboEduc software, allows the programming of several programmable robots to be performed using the R-Educ language. We make it possible for the user to program in the language R-Educ and then translate the code to a language previously registered, compiled and then sent or executed by the robot. To develop this work, we conducted a bibliographic research about the main programming languages used in robotics, as well as their definitions and paradigms, from which it was possible to define a set of patterns considered important for the creation of this environment. Then, in the software development phase, we implemented the development environment, bearing in mind the requirements and functionality defined in the design phase. Finally, to validate the platform, we conducted some trials of programming languages and verificate if the complete cycle was satisfied - registration of language, programming in R-Educ, compilation for the registered language, compilation to the machine code and send the code for the robot
Resumo:
Quadrotors aircraft are composed by four propellers mounted on four engines on a cross or x disposition, and, in this structure, the engines on the same arm spin in the same direction and the other arm in the opposite direction. By rotating each helix generates vertical upward thrust. The control is done by varying the rotational speed of each motor. Among the advantages of this type of vehicle can cite the mechanical simplicity of construction, the high degree of maneuverability and the ability to have vertical takeoffs and landings. The modeling and control of quadrirrotores have been a challenge due to problems such as nonlinearity and coupling between variables. Several strategies have been developed to control this type of vehicle, from the classical control to modern. There are air surveillance applications where a camera is fixed on the vehicle to point forward, where it is desired that the quadrotor moves at a fixed altitude toward the target also pointing forward, which imposes an artificial constraint motion, because it is not desired that it moves laterally, but only forwards or backwards and around its axes . This restriction is similar to the naturally existing on robots powered by wheels with differential drive, which also can not move laterally, due to the friction of the wheels. Therefore, a position control strategy similar to that used in this type of robot could be adapted for aerial robots like quadrotor. This dissertation presents and discusses some strategies for the control of position and orientation of quadrotors found in the literature and proposes a strategy based on dynamic control of mobile robots with differential drive, called the variable reference control. The validity of the proposed strategy is demonstrated through computer simulations
Resumo:
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
Resumo:
Mobile robots need autonomy to fulfill their tasks. Such autonomy is related whith their capacity to explorer and to recognize their navigation environments. In this context, the present work considers techniques for the classification and extraction of features from images, using artificial neural networks. This images are used in the mapping and localization system of LACE (Automation and Evolutive Computing Laboratory) mobile robot. In this direction, the robot uses a sensorial system composed by ultrasound sensors and a catadioptric vision system equipped with a camera and a conical mirror. The mapping system is composed of three modules; two of them will be presented in this paper: the classifier and the characterizer modules. Results of these modules simulations are presented in this paper.
Resumo:
This work describes a ludic proposal for programming learning of industrial robots to be developed by groups of engineering students. Two projects are presented: Tic-tac-toe Opponent Robot and Environmentalist Robot. The first project use competitive search techniques of the Artificial Intelligence, computational vision, electronic and pneumatic concepts for ability decision making for a robotic agent on the tic-tae-toe game. The second project consists of a game that contains a questions and answers database about environmental themes. An algorithm selects the group of questions to be answered by the player, analyses the answers and sends the result to a industrial robot through serial port. According with the player performance, the robot makes congratulation movements and giving a gift to the winner player. Otherwise, the robot makes movements, disapproving the player performance.
Resumo:
The shape modes of a damped-free beam model with a tip rotor are determined by using a dynamical basis that is generated by a fundamental spatial free response. This is a non-classical distributed model for the displacements in the transverse directions of the beam which turns out to be coupled through boundary conditions due to rotation. Numerical calculations are performed by using the Ritz-Rayleigh method with several approximating basis.
Resumo:
The impact of new advanced technology on issues that concern meaningful information and its relation to studies of intelligence constitutes the main topic of the present paper. The advantages, disadvantages and implications of the synthetic methodology developed by cognitive scientists, according to which mechanical models of the mind, such as computer simulations or self-organizing robots, may provide good explanatory tools to investigate cognition, are discussed. A difficulty with this methodology is pointed out, namely the use of meaningless information to explain intelligent behavior that incorporates meaningful information. In this context, it is inquired what are the contributions of cognitive science to contemporary studies of intelligent behavior and how technology may play a role in the analysis of the relationships established by organisms in their natural and social environments. © John Benjamins Publishing Company.
Resumo:
We investigate, from a philosophical perspective, the relation between abductive reasoning and information in the context of biological systems. Emphasis is given to the organizational role played by abductive reasoning in practical activities of embodied embedded agency that involve meaningful information. From this perspective, meaningful information is provisionally characterized as a selforganizing process of pattern generation that constrains coherent action. We argue that this process can be considered as a part of evolutionarily developed learning abilities of organisms in order to help with their survival. We investigate the case of inorganic mechanical systems (like robots), which deal only with stable forms of habits, rather than with evolving learning abilities. Some difficulties are considered concerning the hypothesis that mechanical systems may operate with meaningful information, present in abductive reasoning. Finally, an example of hypotheses creation in the domain of medical sciences is presented in order to illustrate the complexity of abduction in practical reasoning concerning human activities. © 2007 Springer-Verlag Berlin Heidelberg.
Resumo:
This article describes the application of an Artificial Intelligence Planner in a robotized assembly cell that can be integrated to a Flexible Manufacturing System. The objective is to allow different products to be automatically assembled in a single production line with no pre-established assembly plans. The planner function is to generate action plans to the robot, in real time, from two input information: the initial state (disposition of parts of the product in line) and the final state (configuration of the assembled product). Copyright © 2007 IFAC.
Resumo:
This project aims to apply image processing techniques in computer vision featuring an omnidirectional vision system to agricultural mobile robots (AMR) used for trajectory navigation problems, as well as localization matters. To carry through this task, computational methods based on the JSEG algorithm were used to provide the classification and the characterization of such problems, together with Artificial Neural Networks (ANN) for pattern recognition. Therefore, it was possible to run simulations and carry out analyses of the performance of JSEG image segmentation technique through Matlab/Octave platforms, along with the application of customized Back-propagation algorithm and statistical methods in a Simulink environment. Having the aforementioned procedures been done, it was practicable to classify and also characterize the HSV space color segments, not to mention allow the recognition of patterns in which reasonably accurate results were obtained.
Resumo:
This work presents the Petri net-based modeling of an autonomous robot's navigation system used for the application of supplies in agriculture. The model was developed theoretically and implemented through the CPNTools software. It simulates the behavior of the robot, capturing environmental characteristics by means of sensors, making appropriate decisions, and forwarding them to the corresponding actuators. By exciting the model using CPNTools it is possible to simulate situations that the robot might undergo, without the need to expose it to real potentially dangerous situations. ©2009 IEEE.
ANN statistical image recognition method for computer vision in agricultural mobile robot navigation
Resumo:
The main application area in this project, is to deploy image processing and segmentation techniques in computer vision through an omnidirectional vision system to agricultural mobile robots (AMR) used for trajectory navigation problems, as well as localization matters. Thereby, computational methods based on the JSEG algorithm were used to provide the classification and the characterization of such problems, together with Artificial Neural Networks (ANN) for image recognition. Hence, it was possible to run simulations and carry out analyses of the performance of JSEG image segmentation technique through Matlab/Octave computational platforms, along with the application of customized Back-propagation Multilayer Perceptron (MLP) algorithm and statistical methods as structured heuristics methods in a Simulink environment. Having the aforementioned procedures been done, it was practicable to classify and also characterize the HSV space color segments, not to mention allow the recognition of segmented images in which reasonably accurate results were obtained. © 2010 IEEE.