951 resultados para Autonomous mobile robots


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Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Electrotécnica e de Computadores

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Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para a obtenção do grau de Mestre em Engenharia Electrotécnica e de Computadores

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This paper extents the by now classic sensor fusion complementary filter (CF) design, involving two sensors, to the case where three sensors that provide measurements in different bands are available. This paper shows that the use of classical CF techniques to tackle a generic three sensors fusion problem, based solely on their frequency domain characteristics, leads to a minimal realization, stable, sub-optimal solution, denoted as Complementary Filters3 (CF3). Then, a new approach for the estimation problem at hand is used, based on optimal linear Kalman filtering techniques. Moreover, the solution is shown to preserve the complementary property, i.e. the sum of the three transfer functions of the respective sensors add up to one, both in continuous and discrete time domains. This new class of filters are denoted as Complementary Kalman Filters3 (CKF3). The attitude estimation of a mobile robot is addressed, based on data from a rate gyroscope, a digital compass, and odometry. The experimental results obtained are reported.

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In this work the mission control and supervision system developed for the ROAZ Autonomous Surface Vehicle is presented. Complexity in mission requirements coupled with flexibility lead to the design of a modular hierarchical mission control system based on hybrid systems control. Monitoring and supervision control for a vehicle such as ROAZ mission is not an easy task using tools with low complexity and yet powerful enough. A set of tools were developed to perform both on board mission control and remote planning and supervision. “ROAZ- Mission Control” was developed to be used in support to bathymetric and security missions performed in river and at seas.

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This work presents the integration of obstacle detection and analysis capabilities in a coherent and advanced C&C framework allowing mixed-mode control in unmanned surface systems. The collision avoidance work has been successfully integrated in an operational autonomous surface vehicle and demonstrated in real operational conditions. We present the collision avoidance system, the ROAZ autonomous surface vehicle and the results obtained at sea tests. Limitations of current COTS radar systems are also discussed and further research directions are proposed towards the development and integration of advanced collision avoidance systems taking in account the different requirements in unmanned surface vehicles.

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Underwater acoustic networks can be quite effective to establish communication links between autonomous underwater vehicles (AUVs) and other vehicles or control units, enabling complex vehicle applications and control scenarios. A communications and control framework to support the use of underwater acoustic networks and sample application scenarios are described for single and multi-AUV operation.

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Robotica 2012: 12th International Conference on Autonomous Robot Systems and Competitions April 11, 2012, Guimarães, Portugal

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In this paper we introduce a formation control loop that maximizes the performance of the cooperative perception of a tracked target by a team of mobile robots, while maintaining the team in formation, with a dynamically adjustable geometry which is a function of the quality of the target perception by the team. In the formation control loop, the controller module is a distributed non-linear model predictive controller and the estimator module fuses local estimates of the target state, obtained by a particle filter at each robot. The two modules and their integration are described in detail, including a real-time database associated to a wireless communication protocol that facilitates the exchange of state data while reducing collisions among team members. Simulation and real robot results for indoor and outdoor teams of different robots are presented. The results highlight how our method successfully enables a team of homogeneous robots to minimize the total uncertainty of the tracked target cooperative estimate while complying with performance criteria such as keeping a pre-set distance between the teammates and the target, avoiding collisions with teammates and/or surrounding obstacles.

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A crescente necessidade de meios de inspecção e recolha de informação de infraestruturas e do meio ambiente natural, origina o recurso a meios tecnológicos cada vez mais evoluídos. Neste contexto, os robôs móveis autónomos aéreos surgem como uma ferramenta importante. Em particular, os veículos aéreos de asa móvel, pela sua manobrabilidade e controlo podem-se utilizar eficazmente em meios complexos como cenários interiores onde o ambiente é parcialmente controlado. A sua utilização em coordenação com outros veículos robóticos móveis e em particular com a crescente autonomia de decisão, permitem uma eficiência elevada, por exemplo, em tarefas de recolha automática de informação, vigilância, apoio a comunicações, etc. A inexistência de um veículo autónomo de asa móvel no cenário multi-robótico desenvolvido pelo Laboratório de Sistemas Autónomos do Instituto Superior de Engenharia do Porto, aliada às suas aplicações referidas, criou a necessidade do desenvolvimento de um veículo desta gama. Identificou-se, pois, o desenvolvimento de um veículo autónomo aéreo do tipo quadrotor com capacidade de vôo base estabilizado como o problema a resolver. Foi efectuado um levantamento de requisitos do sistema, a caracterização de um veículo autónomo aéreo Vertical Take-off and Landing - VTOL, e efectuado um trabalho de pesquisa a fim de possibilitar o conhecimento das técnicas e tecnologias envolvidas. Tendo em vista o objectivo de controlo e estabilização do veículo, foi efectuada a modelização do sistema que serviu não só para a melhor compreensão da sua dinâmica mas também para o desenvolvimento de um simulador que possibilitou a validação de estratégias de controlo e avaliação de comportamentos do veículo para diferentes cenários. A inexistência de controladores de motores brushless adequada (frequência de controlo), originou o desenvolvimento de um controlador dedicado para motores brushless, motores esses utilizados para a propulsão do veículo. Este controlador permite uma taxa de controlo a uma frequência de 20KHz, possui múltiplas interfaces de comunicação (CAN, RS232, Ethernet, SPI e JTAG), é de reduzido peso e dimensões e modular, visto ter sido implementado em dois módulos, i.e., permite a sua utilização com diferentes interfaces de potência. Projectou-se um veículo autónomo aéreo em termos físicos com a definição da sua arquitectura de hardware e software bem como o sistema de controlo de vôo. O sistema de estabilização de vôo compreende o processamento de informação fornecida por um sistema de navegação inercial, um sonar e o envio de referências de velocidade para cada um dos nós de controlo ligados a um barramento CAN instalado no veículo. A implementação do veículo foi alcançada nas suas vertentes mecânica, de hardware e software. O UAV foi equipado com um sistema computacional dotando-o de capacidades para o desempenho de tarefas previamente analisadas. No presente trabalho, são também tiradas algumas conclusões sobre o desenvolvimento do sistema e sua implementação bem como perspectivada a sua evolução futura no contexto de missões coordenadas de múltiplos veículos robóticos.

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RoboCup was created in 1996 by a group of Japanese, American, and European Artificial Intelligence and Robotics researchers with a formidable, visionary long-term challenge: “By 2050 a team of robot soccer players will beat the human World Cup champion team.” At that time, in the mid 90s, when there were very few effective mobile robots and the Honda P2 humanoid robot was presented to a stunning public for the first time also in 1996, the RoboCup challenge, set as an adversarial game between teams of autonomous robots, was fascinating and exciting. RoboCup enthusiastically and concretely introduced three robot soccer leagues, namely “Simulation,” “Small-Size,” and “Middle-Size,” as we explain below, and organized its first competitions at IJCAI’97 in Nagoya with a surprising number of 100 participants [RC97]. It was the beginning of what became a continously growing research community. RoboCup established itself as a structured organization (the RoboCup Federation www.RoboCup.org). RoboCup fosters annual competition events, where the scientific challenges faced by the researchers are addressed in a setting that is attractive also to the general public. and the RoboCup events are the ones most popular and attended in the research fields of AI and Robotics.RoboCup further includes a technical symposium with contributions relevant to the RoboCup competitions and beyond to the general AI and robotics.

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Proposes a behavior-based scheme for high-level control of autonomous underwater vehicles (AUVs). Two main characteristics can be highlighted in the control scheme. Behavior coordination is done through a hybrid methodology, which takes in advantages of the robustness and modularity in competitive approaches, as well as optimized trajectories

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The estimation of camera egomotion is a well established problem in computer vision. Many approaches have been proposed based on both the discrete and the differential epipolar constraint. The discrete case is mainly used in self-calibrated stereoscopic systems, whereas the differential case deals with a unique moving camera. The article surveys several methods for mobile robot egomotion estimation covering more than 0.5 million samples using synthetic data. Results from real data are also given

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This paper proposes a hybrid coordination method for behavior-based control architectures. The hybrid method takes advantages of the robustness and modularity in competitive approaches as well as optimized trajectories in cooperative ones. This paper shows the feasibility of applying this hybrid method with a 3D-navigation to an autonomous underwater vehicle (AUV). The behaviors are learnt online by means of reinforcement learning. A continuous Q-learning implemented with a feed-forward neural network is employed. Realistic simulations were carried out. The results obtained show the good performance of the hybrid method on behavior coordination as well as the convergence of the behaviors

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This research work deals with the problem of modeling and design of low level speed controller for the mobile robot PRIM. The main objective is to develop an effective educational tool. On one hand, the interests in using the open mobile platform PRIM consist in integrating several highly related subjects to the automatic control theory in an educational context, by embracing the subjects of communications, signal processing, sensor fusion and hardware design, amongst others. On the other hand, the idea is to implement useful navigation strategies such that the robot can be served as a mobile multimedia information point. It is in this context, when navigation strategies are oriented to goal achievement, that a local model predictive control is attained. Hence, such studies are presented as a very interesting control strategy in order to develop the future capabilities of the system

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This paper is focused on the robot mobile platform PRIM (platform robot information multimedia). This robot has been made in order to cover two main needs of our group, on one hand the need for a full open mobile robotic platform that is very useful in fulfilling the teaching and research activity of our school community, and on the other hand with the idea of introducing an ethical product which would be useful as mobile multimedia information point as a service tool. This paper introduces exactly how the system is made up and explains just what the philosophy is behind this work. The navigation strategies and sensor fusion, where machine vision system is the most important one, are oriented towards goal achievement and are the key to the behaviour of the robot