836 resultados para robotics


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In this Thesis, the development of the dynamic model of multirotor unmanned aerial vehicle with vertical takeoff and landing characteristics, considering input nonlinearities and a full state robust backstepping controller are presented. The dynamic model is expressed using the Newton-Euler laws, aiming to obtain a better mathematical representation of the mechanical system for system analysis and control design, not only when it is hovering, but also when it is taking-off, or landing, or flying to perform a task. The input nonlinearities are the deadzone and saturation, where the gravitational effect and the inherent physical constrains of the rotors are related and addressed. The experimental multirotor aerial vehicle is equipped with an inertial measurement unit and a sonar sensor, which appropriately provides measurements of attitude and altitude. A real-time attitude estimation scheme based on the extended Kalman filter using quaternions was developed. Then, for robustness analysis, sensors were modeled as the ideal value with addition of an unknown bias and unknown white noise. The bounded robust attitude/altitude controller were derived based on globally uniformly practically asymptotically stable for real systems, that remains globally uniformly asymptotically stable if and only if their solutions are globally uniformly bounded, dealing with convergence and stability into a ball of the state space with non-null radius, under some assumptions. The Lyapunov analysis technique was used to prove the stability of the closed-loop system, compute bounds on control gains and guaranteeing desired bounds on attitude dynamics tracking errors in the presence of measurement disturbances. The controller laws were tested in numerical simulations and in an experimental hexarotor, developed at the UFRN Robotics Laboratory

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Visual attention is a very important task in autonomous robotics, but, because of its complexity, the processing time required is significant. We propose an architecture for feature selection using foveated images that is guided by visual attention tasks and that reduces the processing time required to perform these tasks. Our system can be applied in bottom-up or top-down visual attention. The foveated model determines which scales are to be used on the feature extraction algorithm. The system is able to discard features that are not extremely necessary for the tasks, thus, reducing the processing time. If the fovea is correctly placed, then it is possible to reduce the processing time without compromising the quality of the tasks outputs. The distance of the fovea from the object is also analyzed. If the visual system loses the tracking in top-down attention, basic strategies of fovea placement can be applied. Experiments have shown that it is possible to reduce up to 60% the processing time with this approach. To validate the method, we tested it with the feature algorithm known as Speeded Up Robust Features (SURF), one of the most efficient approaches for feature extraction. With the proposed architecture, we can accomplish real time requirements of robotics vision, mainly to be applied in autonomous robotics

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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

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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

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In recent years, the radio frequency identification technology (RFID) has gained great interest both industrial communities as scientific communities. Its ability to locate and monitor objects, animals and persons with active or passive tags allows easy development, with good cost-benefice and still presents undeniable benefits in applications ranging from logistics to healthcare, robotics, security, among others. Within this aspect what else comes excelling are RFID tags and the antennas used in RFID readers. Most tags have antennas omnidirectional and are usually manufactured as dipoles modified printed. The primary purpose of a project of antenna for tag is to achieve the required input impedance to perform a good marriage impedance with the load impedance of the chip. Already the objective principal in project of antennas for readers is to achieve reduced sizes and structures with good data transmission capacity. This work brings the numerical characterization of antennas for RFID applications, being these divided into tags RFID and antennas for RFID readers. Three tags RFID and two antennas for RFID readers, found in literature, are analyzed. The analysis of these structures is made using the Method of Waves - WCIP. Initial results found in the literature are compared with those obtained through simulations in WCIP with objective to show that the Method of Waves is able to analyze such structures. To illustrate the results obtained in simulations is presented the behavior of electric and magnetic fields. It also performed a literature review on the characteristics and principles of RFID technology. Suggestions for continuity to this work are presented

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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

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Visual Odometry is the process that estimates camera position and orientation based solely on images and in features (projections of visual landmarks present in the scene) extraced from them. With the increasing advance of Computer Vision algorithms and computer processing power, the subarea known as Structure from Motion (SFM) started to supply mathematical tools composing localization systems for robotics and Augmented Reality applications, in contrast with its initial purpose of being used in inherently offline solutions aiming 3D reconstruction and image based modelling. In that way, this work proposes a pipeline to obtain relative position featuring a previously calibrated camera as positional sensor and based entirely on models and algorithms from SFM. Techniques usually applied in camera localization systems such as Kalman filters and particle filters are not used, making unnecessary additional information like probabilistic models for camera state transition. Experiments assessing both 3D reconstruction quality and camera position estimated by the system were performed, in which image sequences captured in reallistic scenarios were processed and compared to localization data gathered from a mobile robotic platform

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Considering the transition from industrial society to information society, we realize that the digital training that is addressed is currently insufficient to navigate within a digitized reality. As proposed to minimize this problem, this paper assesses, validates and develops the software RoboEduc to work with educational robotics with the main differential programming of robotic devices in levels, considering the specifics of reality training . One of the emphases of this work isthe presentation of materials and procedures involving the development, analysis and evolution of this software. For validation of usability tests were performed, based on analysis of these tests was developed version 4.0 of RoboEduc

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This work addresses the dynamic control problem of two-wheeled differentially driven non-holonomic mobile robot. Strategies for robot positioning control and robot orientating control are presented. Such strategies just require information about the robot con¯guration (x, y and teta), which can be collected by an absolute positioning system. The strategies development is related to a change on the controlled variables for such systems, from x, y and teta to s (denoting the robot linear displacement) and teta, and makes use of the polar coordinates representation for the robot kinematic model. Thus, it is possible to obtain a linear representation for the mobile robot dynamic model and to develop such strategies. It is also presented that such strategies allow the use of linear controllers to solve the control problem. It is shown that there is flexibility to choice the linear controller (P, PI, PID, Model Matching techniques, others) to be implemented. This work presents an introduction to mobile robotics and their characteristics followed by the control strategies development and controllers design. Finally, simulated and experimental results are presented and commented

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The main task and one of the major mobile robotics problems is its navigation process. Conceptualy, this process means drive the robot from an initial position and orientation to a goal position and orientation, along an admissible path respecting the temporal and velocity constraints. This task must be accomplished by some subtasks like robot localization in the workspace, admissible path planning, trajectory generation and motion control. Moreover, autonomous wheeled mobile robots have kinematics constraints, also called nonholonomic constraints, that impose the robot can not move everywhere freely in its workspace, reducing the number of feasible paths between two distinct positions. This work mainly approaches the path planning and trajectory generation problems applied to wheeled mobile robots acting on a robot soccer environment. The major dificulty in this process is to find a smooth function that respects the imposed robot kinematic constraints. This work proposes a path generation strategy based on parametric polynomials of third degree for the 'x' and 'y' axis. The 'theta' orientation is derived from the 'y' and 'x' relations in such a way that the generated path respects the kinematic constraint. To execute the trajectory, this work also shows a simple control strategy acting on the robot linear and angular velocities

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In multi-robot systems, both control architecture and work strategy represent a challenge for researchers. It is important to have a robust architecture that can be easily adapted to requirement changes. It is also important that work strategy allows robots to complete tasks efficiently, considering that robots interact directly in environments with humans. In this context, this work explores two approaches for robot soccer team coordination for cooperative tasks development. Both approaches are based on a combination of imitation learning and reinforcement learning. Thus, in the first approach was developed a control architecture, a fuzzy inference engine for recognizing situations in robot soccer games, a software for narration of robot soccer games based on the inference engine and the implementation of learning by imitation from observation and analysis of others robotic teams. Moreover, state abstraction was efficiently implemented in reinforcement learning applied to the robot soccer standard problem. Finally, reinforcement learning was implemented in a form where actions are explored only in some states (for example, states where an specialist robot system used them) differently to the traditional form, where actions have to be tested in all states. In the second approach reinforcement learning was implemented with function approximation, for which an algorithm called RBF-Sarsa($lambda$) was created. In both approaches batch reinforcement learning algorithms were implemented and imitation learning was used as a seed for reinforcement learning. Moreover, learning from robotic teams controlled by humans was explored. The proposal in this work had revealed efficient in the robot soccer standard problem and, when implemented in other robotics systems, they will allow that these robotics systems can efficiently and effectively develop assigned tasks. These approaches will give high adaptation capabilities to requirements and environment changes.

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We propose a robotics simulation platform, named S-Educ, developed specifically for application in educational robotics, which can be used as an alternative or in association with robotics kits in classes involving the use of robotics. In the usually known approach, educational robotics uses robotics kits for classes which generally include interdisciplinary themes. The idea of this work is not to replace these kits, but to use the developed simulator as an alternative, where, for some reason, the traditional kits cannot be used, or even to use the platform in association with these kits. To develop the simulator, initially, we conducted research in the literature on the use of robotic simulators and robotic kits, facing the education sector, from which it was possible to define a set of features considered important for creating such a tool. Then, on the software development phase, the simulator S-Educ was implemented, taking into account the requirements and features defined in the design phase. Finally, to validate the platform, several tests were conducted with teachers, students and lay adults, in which it was used the simulator S-Educ, to evaluate its use in educational robotics classes. The results show that robotic simulator allows a reduction of financial costs, facilitate testing and reduce robot damage inherent to its use, in addition to other advantages. Furthermore, as a contribution to the community, the proposed tool can be used to increase adhesion of Brazilian schools to the methodologies of educational robotics or to robotics competitions

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A challenge that remains in the robotics field is how to make a robot to react in real time to visual stimulus. Traditional computer vision algorithms used to overcome this problem are still very expensive taking too long when using common computer processors. Very simple algorithms like image filtering or even mathematical morphology operations may take too long. Researchers have implemented image processing algorithms in high parallelism hardware devices in order to cut down the time spent in the algorithms processing, with good results. By using hardware implemented image processing techniques and a platform oriented system that uses the Nios II Processor we propose an approach that uses the hardware processing and event based programming to simplify the vision based systems while at the same time accelerating some parts of the used algorithms

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The objective of the dissertation was the realization of kinematic modeling of a robotic wheelchair using virtual chains, allowing the wheelchair modeling as a set of robotic manipulator arms forming a cooperative parallel kinematic chain. This document presents the development of a robotic wheelchair to transport people with special needs who overcomes obstacles like a street curb and barriers to accessibility in streets and avenues, including the study of assistive technology, parallel architecture, kinematics modeling, construction and assembly of the prototype robot with the completion of a checklist of problems and barriers to accessibility in several pathways, based on rules, ordinances and existing laws. As a result, simulations were performed on the chair in various states of operation to accomplish the task of going up and down stair with different measures, making the proportional control based on kinematics. To verify the simulated results we developed a prototype robotic wheelchair. This project was developed to provide a better quality of life for people with disabilities

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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