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Made available in DSpace on 2016-08-31T13:33:46Z (GMT). No. of bitstreams: 1 TayaraCPB_Dissert.pdf: 1984521 bytes, checksum: 5a46c1781124a49b404a083b87b969bd (MD5) Previous issue date: 2015-08-28 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / With advances in technology and the popularization of the use of Unmanned Aerial Vehicles (UAV's) so does the need to use more robust and more effective control techniques. Among the various types of unmanned aerial vehicles, this paper will focus on quadrotor model, which has a mechanical structure in the form of x, whose ends have an engine and propeller assembly, where the rotation of this group is responsible for the lift and the movements developed by quadrotor. This feeling, aiming to apply drivers that provide stability to the dynamic system. This study aims to conduct mathematical modeling using the Euler-Lagrange. With this, it is proposed a PID controller (Proportional Integral Derivative) to maintain stable the three orientation angles and height to a desired value. The development of the proposed controller will be validated via simulation confirming the application feasibility of the technique presented stability / Com o avanço tecnológico e a popularização do uso dos Veículos Aéreos Não Tripulados (VANT s) cresce também a necessidade do uso de técnicas de controle mais robustas e mais eficazes. Dentre os mais diversos tipos de veículos aéreos não tripulados, este trabalho irá focar no modelo do quadrotor, que possui uma estrutura mecânica em forma de cruz, cujas extremidades têm um conjunto de motor e hélice, onde a rotação desse conjunto é responsável pela força de sustentação e pelos movimentos desenvolvidos pelo mesmo. Objetivando aplicar controladores que proporcione estabilidade ao sistema dinâmico deste veiculo aéreo. O presente trabalho tem como objetivo realizar a modelagem matemática deste sistema usando as equações de Euler-Lagrange. Tendo isso, é proposto um controlador PID (Proporcional Integral Derivativo) para manter os três ângulos de orientação estáveis e a altura em um valor desejado. O desenvolvimento do controlador proposto será validado via simulação confirmando a viabilidade da aplicação da técnica de estabilidade apresentada

[pt] Com recentes avanços em poder computacional, o uso de novos modelos de controle complexos se tornou viável para realizar o controle de quadrotores. Um destes métodos é o aprendizado por reforço profundo (do inglês, Deep Reinforcement Learning, DRL), que pode produzir uma política de controle que atende melhor as não-linearidades presentes no modelo do quadrotor que um método de controle tradicional. Umas das não-linearidades importantes presentes em veículos aéreos transportadores de carga são as propriedades variantes no tempo, como tamanho e massa, causadas pela adição e remoção de carga. A abordagem geral e domínio-agnóstica de um controlador por DRL também o permite lidar com navegação visual, na qual a estimação de dados de posição é incerta. Neste trabalho, aplicamos um algorítmo de Soft Actor- Critic com o objeivo de projetar controladores para um quadrotor a fim de realizar tarefas que reproduzem os desafios citados em um ambiente virtual. Primeiramente, desenvolvemos dois controladores de condução por waypoint: um controlador de baixo nível que atua diretamente em comandos para o motor e um controlador de alto nível que interage em cascata com um controlador de velocidade PID. Os controladores são então avaliados quanto à tarefa proposta de coleta e alijamento de carga, que, dessa forma, introduz uma variável variante no tempo. Os controladores concebidos são capazes de superar o controlador clássico de posição PID com ganhos otimizados no curso proposto, enquanto permanece agnóstico em relação a um conjunto de parâmetros de simulação. Finalmente, aplicamos o mesmo algorítmo de DRL para desenvolver um controlador que se utiliza de dados visuais para completar um curso de corrida em uma simulação. Com este controlador, o quadrotor é capaz de localizar portões utilizando uma câmera RGB-D e encontrar uma trajetória que o conduz a atravessar o máximo possível de portões presentes no percurso. / [en] With recent advances in computational power, the use of novel, complex control models has become viable for controlling quadrotors. One such method is Deep Reinforcement Learning (DRL), which can devise a control policy that better addresses non-linearities in the quadrotor model than traditional control methods. An important non-linearity present in payload carrying air vehicles are the inherent time-varying properties, such as size and mass, caused by the addition and removal of cargo. The general, domain-agnostic approach of the DRL controller also allows it to handle visual navigation, in which position estimation data is unreliable. In this work, we employ a Soft Actor-Critic algorithm to design controllers for a quadrotor to carry out tasks reproducing the mentioned challenges in a virtual environment. First, we develop two waypoint guidance controllers: a low-level controller that acts directly on motor commands and a high-level controller that interacts in cascade with a velocity PID controller. The controllers are then evaluated on the proposed payload pickup and drop task, thereby introducing a timevarying variable. The controllers conceived are able to outperform a traditional positional PID controller with optimized gains in the proposed course, while remaining agnostic to a set of simulation parameters. Finally, we employ the same DRL algorithm to develop a controller that can leverage visual data to complete a racing course in simulation. With this controller, the quadrotor is able to localize gates using an RGB-D camera and devise a trajectory that drives it to traverse as many gates in the racing course as possible.

Made available in DSpace on 2014-12-17T14:55:09Z (GMT). No. of bitstreams: 1 JoaoPFG_DISSERT.pdf: 1458535 bytes, checksum: fae41c0cfc4b0b09e65c1f69ec230a28 (MD5) Previous issue date: 2012-12-19 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior / A Quadrotor is an Unmanned Aerial Vehicle (UAV) equipped with four rotors distributed on a simple mechanical "X"form structure. The aim of this work is to build and stabilize a Quadrotor aircraft in the roll, pitch and yaw angles at a certain altitude. The stabilization control approach is based on a transformation in the input variables in order to perform a decoupled control. The proposed strategy is based on breaking the control problem into two hierarchical levels: A lower level, object of this work, maintains the desired altitude an angles of the vehicle while the higher level establishes appropriate references to the lower level, performing the desired movements. A hardware and software architecture was specially developed and implemented for an experimental prototype used to test and validate the proposed control approach / Um Quadrirrotor ? um Ve?culo A?reo N?o Tripulado (VANT) dotado de quatro rotores distribu?dos nas extremidades de uma estrutura mec?nica simples em forma de "X". O objetivo desse trabalho ? construir e estabilizar uma aeronave desse tipo, com alta capacidade de carga, em uma determinada altitude, sob ?ngulos de rolagem, guinada e arfagem pr?-definidos. A abordagem de controle de estabiliza??o baseia-se numa transforma??o das vari?veis de entrada do sistema a fim de realizar o controle de forma desacoplada. A estrat?gia proposta se baseia na divis?o do problema de controle em dois n?veis hier?rquicos: o n?vel inferior, objeto deste trabalho, mant?m os ?ngulos e a altitude do ve?culo em valores desejados, enquanto o n?vel superior estabelece refer?ncias adequadas para o n?vel inferior, de forma a executar os movimentos desejados Uma arquitetura de hardware e software foi especialmente desenvolvida e implementada para um prot?tipo experimental usado para testar e validar a abordagem de controle proposta

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / O presente trabalho objetiva o desenvolvimento de uma estratégia de controle adaptativa capaz de estabilizar e atuar no cumprimento de trajetórias de um veículo quadricóptero. O quadricóptero é definido como uma aeronave de pousos de decolagens verticais (VTOL) e emergiu a partir da segunda metade da década de 2000 como uma plataforma promissora para utilização em diversas finalidades devido, principalmente, à sua simplicidade mecânica, alto payload e robustez. Por isso, essa aeronave tem sido vastamente explorada desde então nas publicações da área, preocupando-se, como este trabalho, em propor metodologias numéricas para aprimorar a autonomia e confiabilidade na utilização prática destes veículos. O modelo matemático do helicóptero foi obtido a partir do formalismo de Euler- Lagrange, considerando um corpo rígido, simétrico e tomando a origem do sistema de coordenadas coincidente com o centro de gravidade do veículo. Como forma de se obter um modelo mais fiel à situação real de voo, o Efeito Giroscópio sobre corpo e as hélices foi considerado. Sob a ótica da engenharia de controle, é considerado um sistema subatuado por possuir 4 entradas (associadas às quatro velocidades angulares dos rotores) e seis variáveis de estado (correspondentes às coordenadas generalizadas da mecânica lagrangeana). A partir do modelo obtido, um simulador foi desenvolvido na plataforma Simulink® como método para aferir sobre a eficácia das estratégias de controle propostas. Inicialmente, foi efetivada a estabilização do veículo por um controlador PID clássico e, em seguida, os resultados foram comparados com os dados presentes na literatura a fim de garantir o bom funcionamento da rotina desenvolvida. Finalmente, uma estratégia de controle PID adaptativo foi proposta a partir da implementação de programação heurística baseada em Algoritmos Genéticos para identificar os ganhos ideais dos controladores das coordenadas z, x e y. Os resultados apontaram um considerável ganho de desempenho do método adaptativo sobre o PID clássico para estabilização e seguimento de trajetórias de um veículo quadrirrotor na presença de variação de massa. / This work aims the development of an adaptive control strategy on stabilization and path tracking tasks of a quadrotor vehicle. The quadrotor is defined as a Vertical Take Off and Landing (VTOL) aircraft and it has emerged, in the second half of the 2000s as a promising platform for use in many purposes, mainly due to its mechanical simplicity, high payload and robustness. Therefore, this aircraft has been widely exploited on this area, which researches has focusing, as this work , to propose numerical methods in order to improve the autonomy and reliability in practical use of these vehicles. The helicopter model of the helicopter was obtained from the Euler-Lagrange formalism, considering it as a rigid body, symmetrical and taking the origin of the coordinate system coincides with the center of gravity of the vehicle. In order to obtain a more accurate model compared to the actual flight situation, the Gyro effect on body and propellers was considered. From the perspective of control engineering, it is considered an underactuated system which has 4 inputs (associated with four angular velocities of the rotors) and six state variables (corresponding to generalized coordinates of Lagrangian mechanics) A simulator was developed on Simulink® platform evaluated from the model obtained as a way to check on the effectiveness of the proposed control strategies. Initially, it was implemented a classic PID controller in order to stabilize the, and then the results were compared to the data present in the literature in order to ensure the reliability of the routine implemented. Lastly, an adaptive PID control strategy was proposed from the implementation of heuristic programming based on genetic algorithms to identify optimal gains controllers to the coordinates z , x and y subsystems. The results indicated a significant performance gain of the adaptive method over the classic PID for stabilization and path tracking tasks of a quadrirrotor vehicle in the presence of mass variation. / Dissertação (Mestrado)

Submitted by André Santos (andrehls@hotmail.com) on 2018-09-25T14:05:58Z No. of bitstreams: 4 license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Dissertacão_Andre_Henrique.pdf: 2371704 bytes, checksum: dc85aaa1a6b0fa72681a7a7b1a171ca4 (MD5) Carta_Autodeposito.pdf: 555246 bytes, checksum: 144c46025502c11031e4127f2052153a (MD5) FolhadeAprovação_André.pdf: 464080 bytes, checksum: 36bff5c43916314867debb8d04c55726 (MD5) / Approved for entry into archive by PPGEE Engenharia Elétrica (mestrado_engeletrica@ufam.edu.br) on 2018-09-25T14:38:57Z (GMT) No. of bitstreams: 4 license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Dissertacão_Andre_Henrique.pdf: 2371704 bytes, checksum: dc85aaa1a6b0fa72681a7a7b1a171ca4 (MD5) Carta_Autodeposito.pdf: 555246 bytes, checksum: 144c46025502c11031e4127f2052153a (MD5) FolhadeAprovação_André.pdf: 464080 bytes, checksum: 36bff5c43916314867debb8d04c55726 (MD5) / Rejected by Divisão de Documentação/BC Biblioteca Central (ddbc@ufam.edu.br), reason: Os Campos *Identificador único do Autor* e *Identificador único do orientador* devem ser preenchido com CPF ou Matrícula ou RG ou Passaporte... Favor, retorne ao sistema e edite as informações... on 2018-09-25T17:46:43Z (GMT) / Submitted by André Santos (andrehls@hotmail.com) on 2018-09-25T18:21:06Z No. of bitstreams: 4 Dissertacão_Andre_Henrique.pdf: 2371704 bytes, checksum: dc85aaa1a6b0fa72681a7a7b1a171ca4 (MD5) Carta_Autodeposito.pdf: 555246 bytes, checksum: 144c46025502c11031e4127f2052153a (MD5) FolhadeAprovação_André.pdf: 464080 bytes, checksum: 36bff5c43916314867debb8d04c55726 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Approved for entry into archive by PPGEE Engenharia Elétrica (mestrado_engeletrica@ufam.edu.br) on 2018-09-27T14:01:50Z (GMT) No. of bitstreams: 4 Dissertacão_Andre_Henrique.pdf: 2371704 bytes, checksum: dc85aaa1a6b0fa72681a7a7b1a171ca4 (MD5) Carta_Autodeposito.pdf: 555246 bytes, checksum: 144c46025502c11031e4127f2052153a (MD5) FolhadeAprovação_André.pdf: 464080 bytes, checksum: 36bff5c43916314867debb8d04c55726 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Approved for entry into archive by Divisão de Documentação/BC Biblioteca Central (ddbc@ufam.edu.br) on 2018-09-27T15:27:44Z (GMT) No. of bitstreams: 4 Dissertacão_Andre_Henrique.pdf: 2371704 bytes, checksum: dc85aaa1a6b0fa72681a7a7b1a171ca4 (MD5) Carta_Autodeposito.pdf: 555246 bytes, checksum: 144c46025502c11031e4127f2052153a (MD5) FolhadeAprovação_André.pdf: 464080 bytes, checksum: 36bff5c43916314867debb8d04c55726 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Made available in DSpace on 2018-09-27T15:27:44Z (GMT). No. of bitstreams: 4 Dissertacão_Andre_Henrique.pdf: 2371704 bytes, checksum: dc85aaa1a6b0fa72681a7a7b1a171ca4 (MD5) Carta_Autodeposito.pdf: 555246 bytes, checksum: 144c46025502c11031e4127f2052153a (MD5) FolhadeAprovação_André.pdf: 464080 bytes, checksum: 36bff5c43916314867debb8d04c55726 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2018-08-31 / In this work approaches the development altitude control for a low-cost quadrotor vehicle. The identification of the model of the altitude dynamics of the quadrotor using the relay method is presented. This method is also a tool in the tuning of a PID controller implemented for dynamics model. Comparisons of controller performances, designed for the identified and mathematically modeled plant, were analyzed, in addition to the performance of the controller tuned by the Relay direct method, without the need for the altitude model. In the experiments, transient response performance parameters were evaluated for a step-type reference input. In addition, the behavior of the compensated altitude for a trapezoidal reference trajectory was evaluated. The results showed that the technique employed is, besides simple, efficient for this type of system. / Neste trabalho é abordado o desenvolvimento de um controlador de altitude para um veículo quadrirrotor de baixo custo. A identificação do modelo da dinâmica de altitude do quadrirrotor é realizada utilizando o método do relé. Esse método também é uma ferramenta de auxílio na sintonia de um controlador PID implementado para modelo da dinâmica. Comparações dos desempenhos do controlador, realizados para a planta identificada e modelada matematicamente, foram analisadas, além do desempenho do controlador sintonizado pelo método direto do Relé, esse sem a necessidade do modelo de altitude. Nos experimentos foram avaliados parâmetros de desempenho da resposta em regime transitório para uma entrada de referência do tipo degrau. Além disso, foi avaliado o comportamento da altitude compensada para uma trajetória de referência trapezoidal. Os resultados mostraram que a técnica empregada é, além de simples, eficiente para este tipo de sistema.

Ce manuscrit traite de la conception d’un robot quadrirotor bio-inspiré. Ce robot, nommé QuadMorphing, s’inspire de l’oiseau et possède la capacité de se replier en vol afin de diminuer son envergure. Cette particularité est intéressante pour des problématiques d’évitement d’obstacles dans des milieux encombrés.Le travail présenté ici contient une présentation du robot où la plateforme mécatronique y est décrite en détails. Puis, des résultats expérimentaux sont présentés et commentés afin de quantifier les performances du prototype QuadMorphing durant des scénarios de franchissement d’obstacles.La deuxième partie de cette thèse traite de l’estimation de la taille d’obstacles en vol grâce à une perception visuelle monoculaire. Deux algorithmes d’estimation ont été simulés afin d’être validés pour être ensuite mis en place sur une nouvelle version du robot qui a été testée expérimentalement. Ces estimations permettent par la suite de rendre le robot plus autonome pour éviter les collisions avec son environnement et actionner son système de changement de forme si cela est nécessaire. / This paper describes a bio-inspired quadrotor design. This robot, called QuadMorphing, is inspired by birds and has the ability to fold its mechanical structure to reduce its wingspan during the flight. This feature could be useful for obstacle avoidance task in cluttered environments.The work presented here contains a full description of the mechatronic structure. Then, experimental results are presented and discussed in order to quantify the QuadMorphing performances during obstacle avoidance scenarios.The second part of this thesis deals with estimating obstacle size during flight using monocular visual perception. Two estimation algorithms were simulated in order to be validated and then implemented for experimental testing on a new version of the robot. In order to make the robot autonomous, the estimation of the size of the obstacle allows the robot to avoid collisions with its environment and to perform its morphological reduction if necessary.

This work considers an aerial robot system composed of an Unmanned Aerial Vehicle (UAV) and a rigid manipulator, to be employed in mobile manipulation tasks. The strategy adopted for accomplishing the aerial manipulation is a decomposition of the previous system in two decoupled subsystems: one concerning the center of mass of the aerial robot; and another concerning the manipulator's orientation. Two Lyapunov-based controllers are developed, using a back stepping procedure, for solving the trajectory tracking problems related to the two subsystems. In the controller design, three inputs are assumed available: a translational acceleration along a body direction of the UAV; an angular velocity vector of this body rotation; and, finally, a torque at the spherical, or revolute, joint connecting the UAV and the manipulator. The first two inputs are generated by the same controller in order to drive the center of mass on a desired trajectory; while a second controller drives, through the third input, the manipulator's orientation to track a desired orientation. Formal stability proofs are provided that guarantee asymptotic trajectory tracking. Finally, the proposed control strategy is experimentally tested and validated.

In this thesis two methods were developed for precise maritime landing of an autonomous multirotor aircraft based on real-time kinematic (RTK) Global Navigation Satellite System (GNSS). The first method called RTK-localized method (RLM) uses RTK GNSS measurements to localize a sea vessel and execute the landing. RLM was demonstrated outdoors in hardware and landed on a physically simulated boat called a mock-boat with an average landing error of 9.7 cm. The mock-boat was actuated to have boat-like motion and a forward velocity of ~2 m/s. This method showed that accurate landing is possible with RTK GNSS as the primary means of localizing a sea vessel. The localization was unaided by non-GNSS sensors or an estimator, but lacked full attitude estimation and measurement smoothing. The second method was called RTK-Estimation Method (REM) and provides a more complete and robust solution, particularly at sea. It includes a base (landing pad) estimator to fuse RTK GNSS measurements with a dynamic model of a sea vessel. In contrast to RLM, the estimator provides full attitude estimation and measurement smoothing. The base estimator consists of an EKF in conjunction with a complimentary filter and estimates the relative position, attitude, and velocity of a moving target using RTK GNSS and inertial measurements alone. REM was demonstrated outdoors in hardware for 18 flight tests. The same mock-boat from RLM was used as a substitute for a sea vessel, and the boat motion varied between tests. These dynamics were recorded and performances were compared. The rate of success was high given moderate mock-boat motion and degraded with more aggressive motion. Tests were conducted with forward velocities from 0 to 3 m/s and moderate to high wave like motion. Over all tests for REM, the multirotor landed with an average accuracy of 12.7 cm. The methods described depart from common methods given that the only sensors involved for tracking the sea vessel were RTK GNSS receivers and inertial measurement units. Most current methods rely on computer vision, and can fail in poor lighting conditions, in the presence of ocean spray, and other scenarios. The given solutions do not fail under such conditions. The multirotor was equipped with a standard off-the-shelf autopilot, PX4, and the methods function with common control and estimation schemes. The two methods are capable of landing on relatively small landing pads, on the order of 1 m by 1 m, at sea using measurements from satellites thousands of kilometers away.

Quad-rotor micro-UAVs have become an important tool in the field of indoor UAV research. Indoor flight poses problems not experienced in outdoor applications. The ability to be location- and movement-aware is paramount because of the close proximity of obstacles (walls, doorways, desks). The Helio-copter, an indoor quad-rotor platform that utilizes a compact FPGA board called Helios has been developed in the Robotic Vision Lab at Brigham Young University. Helios allows researchers to perform on-board vision processing and feature tracking without the aid of a ground station or wireless transmission. Using this on-board feature tracking system a drift stabilization control system has been developed that allows indoor flight of the Helio-copter without tethers. The Helio-copter uses an IMU to maintain level attitude while processing camera images on the FPGA. The FPGA then computes translation, scale, and rotation deviations from camera image feedback. An on-board system has been developed to control yaw, altitude and drift based solely on the vision sensors. Preliminary testing shows the Helio-copter capable of maintaining level, stable flight within a 6 foot by 6 foot area for over 40 seconds without human intervention using basic PID loop structures with minor tuning. The integration of the vision system into the control structures is explained.