Modeling, identification and navigation of autonomous air vehicles

The main interest of this work is autonomous navigation of autonomous air vehicles, specifically quadrotor helicopters (quadrocopters), and the focus is on convergence to a target destination with collision avoidance. The controller computes a collision-free path leading to the target position and is based on a navigation function approach and waypoints are followed exploiting PID controller

Aerial Robotics for Inspection and Maintenance

Aerial robots with perception, navigation, and manipulation capabilities are extending the range of applications of drones, allowing the integration of different sensor devices and robotic manipulators to perform inspection and maintenance operations on infrastructures such as power lines, bridges, viaducts, or walls, involving typically physical interactions on flight. New research and technological challenges arise from applications demanding the benefits of aerial robots, particularly in outdoor environments. This book collects eleven papers from different research groups from Spain, Croatia, Italy, Japan, the USA, the Netherlands, and Denmark, focused on the design, development, and experimental validation of methods and technologies for inspection and maintenance using aerial robots

Use of Unmanned Aerial Systems in Civil Applications

Interest in drones has been exponentially growing in the last ten years and these machines are often presented as the optimal solution in a huge number of civil applications (monitoring, agriculture, emergency management etc). However the promises still do not match the data coming from the consumer market, suggesting that the only big field in which the use of small unmanned aerial vehicles is actually profitable is the video-makers’ one. This may be explained partly with the strong limits imposed by existing (and often "obsolete") national regulations, but also - and pheraps mainly - with the lack of real autonomy. The vast majority of vehicles on the market nowadays are infact autonomous only in the sense that they are able to follow a pre-determined list of latitude-longitude-altitude coordinates. The aim of this thesis is to demonstrate that complete autonomy for UAVs can be achieved only with a performing control, reliable and flexible planning platforms and strong perception capabilities; these topics are introduced and discussed by presenting the results of the main research activities performed by the candidate in the last three years which have resulted in 1) the design, integration and control of a test bed for validating and benchmarking visual-based algorithm for space applications; 2) the implementation of a cloud-based platform for multi-agent mission planning; 3) the on-board use of a multi-sensor fusion framework based on an Extended Kalman Filter architecture

Aerial Vehicles

This book contains 35 chapters written by experts in developing techniques for making aerial vehicles more intelligent, more reliable, more flexible in use, and safer in operation.It will also serve as an inspiration for further improvement of the design and application of aeral vehicles. The advanced techniques and research described here may also be applicable to other high-tech areas such as robotics, avionics, vetronics, and space

Safe and accurate MAV Control, navigation and manipulation

This work focuses on the problem of precise, aggressive and safe Micro Aerial Vehicle (MAV) navigation as well as deployment in applications which require physical interaction with the environment. To address these issues, we propose three different MAV model based control algorithms that rely on the concept of receding horizon control. As a starting point, we present a computationally cheap algorithm which utilizes an approximate linear model of the system around hover and is thus maximally accurate for slow reference maneuvers. Aiming at overcoming the limitations of the linear model parameterisation, we present an extension to the first controller which relies on the true nonlinear dynamics of the system. This approach, even though computationally more intense, ensures that the control model is always valid and allows tracking of full state aggressive trajectories. The last controller addresses the topic of aerial manipulation in which the versatility of aerial vehicles is combined with the manipulation capabilities of robotic arms. The proposed method relies on the formulation of a hybrid nonlinear MAV-arm model which also takes into account the effects of contact with the environment. Finally, in order to enable safe operation despite the potential loss of an actuator, we propose a supervisory algorithm which estimates the health status of each motor. We further showcase how this can be used in conjunction with the nonlinear controllers described above for fault tolerant MAV flight. While all the developed algorithms are formulated and tested using our specific MAV platforms (consisting of underactuated hexacopters for the free flight experiments, hexacopter-delta arm system for the manipulation experiments), we further discuss how these can be applied to other underactuated/overactuated MAVs and robotic arm platforms. The same applies to the fault tolerant control where we discuss different stabilisation techniques depending on the capabilities of the available hardware. Even though the primary focus of this work is on feedback control, we thoroughly describe the custom hardware platforms used for the experimental evaluation, the state estimation algorithms which provide the basis for control as well as the parameter identification required for the formulation of the various control models. We showcase all the developed algorithms in experimental scenarios designed to highlight the corresponding strengths and weaknesses as well as show that the proposed methods can run in realtime on commercially available hardware.Open Acces

Models, algorithms and architectures for cooperative manipulation with aerial and ground robots

Les dernières années ont vu le développement de recherches portant sur l'interaction physique entre les robots aériens et leur environnement, accompagné de l'apparition de nombreux nouveaux systèmes mécaniques et approches de régulation. La communauté centrée autour de la robotique aérienne observe actuellement un déplacement de paradigmes des approches classiques de guidage, de navigation et de régulation vers des tâches moins triviales, telle le développement de l'interaction physique entre robots aériens et leur environnement. Ceci correspond à une extension des tâches dites de manipulation, du sol vers les airs. Cette thèse contribue au domaine de la manipulation aérienne en proposant un nouveau concept appelé MAGMaS, pour " Multiple Aerial Ground Manipulator System ". Les motivations qui ont conduites à l'association de manipulateurs terrestres et aériens pour effectuer des tâches de manipulation coopérative, résident dans une volonté d'exploiter leurs particularités respectives. Les manipulateurs terrestres apportant leur importante force et les manipulateurs aériens apportant leur vaste espace de travail. La première contribution de cette thèse présente une modélisation rigoureuse des MAGMaS. Les propriétés du système ainsi que ses possibles extensions sont discutées. Les méthodes de planning, d'estimation et de régulation nécessaire à l'exploitation des MAGMaS pour des tâches de manipulation collaborative sont dérivées. Ce travail propose d'exploiter les redondances des MAGMaS grâce à un algorithme optimal d'allocation de forces entre les manipulateurs. De plus, une méthode générale d'estimation de forces pour robots aériens est introduite. Toutes les techniques et les algorithmes présentés dans cette thèse sont intégrés dans une architecture globale, utilisée à la fois pour la simulation et la validation expérimentale. Cette architecture est en outre augmentée par l'addition d'une structure de télé-présence, afin de permettre l'opération à distances des MAGMaS. L'architecture générale est validée par une démonstration de levage de barre, qui est une application représentative des potentiels usages des MAGMaS. Une autre contribution relative au développement des MAGMaS consiste en une étude exploratoire de la flexibilité dans les objets manipulés par un MAGMaS. Un modèle du phénomène vibratoire est dérivé afin de mettre en exergue ses propriétés en termes de contrôle. La dernière contribution de cette thèse consiste en une étude exploratoire sur l'usage des actionneurs à raideur variable dans les robots aériens, dotant ces systèmes d'une compliance mécanique intrinsèque et de capacité de stockage d'énergie. Les fondements théoriques sont associés à la synthèse d'un contrôleur non-linéaire. L'approche proposée est validée par le biais d'expériences reposant sur l'intégration d'un actionneur à raideur variable léger sur un robot aérien.In recent years, the subject of physical interaction for aerial robots has been a popular research area with many new mechanical designs and control approaches being proposed. The aerial robotics community is currently observing a paradigm shift from classic guidance, navigation, and control tasks towards more unusual tasks, for example requesting aerial robots to physically interact with the environment, thus extending the manipulation task from the ground into the air. This thesis contributes to the field of aerial manipulation by proposing a novel concept known has Multiple Aerial-Ground Manipulator System or MAGMaS, including what appears to be the first experimental demonstration of a MAGMaS and opening a new route of research. The motivation behind associating ground and aerial robots for cooperative manipulation is to leverage their respective particularities, ground robots bring strength while aerial robots widen the workspace of the system. The first contribution of this work introduces a meticulous system model for MAGMaS. The system model's properties and potential extensions are discussed in this work. The planning, estimation and control methods which are necessary to exploit MAGMaS in a cooperative manipulation tasks are derived. This works proposes an optimal control allocation scheme to exploit the MAGMaS redundancies and a general model-based force estimation method is presented. All of the proposed techniques reported in this thesis are integrated in a global architecture used for simulations and experimental validation. This architecture is extended by the addition of a tele-presence framework to allow remote operations of MAGMaS. The global architecture is validated by robust demonstrations of bar lifting, an application that gives an outlook of the prospective use of the proposed concept of MAGMaS. Another contribution in the development of MAGMaS consists of an exploratory study on the flexibility of manipulated loads. A vibration model is derived and exploited to showcase vibration properties in terms of control. The last contribution of this thesis consists of an exploratory study on the use of elastic joints in aerial robots, endowing these systems with mechanical compliance and energy storage capabilities. Theoretical groundings are associated with a nonlinear controller synthesis. The proposed approach is validated by experimental work which relies on the integration of a lightweight variable stiffness actuator on an aerial robot

In-Flight Learning Based Flight Control of an Unmanned Aircraft System

Title from PDF of title page viewed June 3, 2019Dissertation advisor: Travis FieldsVitaIncludes bibliographical references (pages 128-137)Thesis (PH.D.)--School of Computing and Engineering. University of Missouri--Kansas City, 2018Unmanned Aerial Vehicles (UAVs) popularity has increased substantially in the last few years. UAVs capabilities continue to improve as a result of advances in battery technology, communication, navigation systems and electronics. Increased popularity has driven researchers to improve UAVs reliability and safety which is reflected by the number of publications and accelerating educational programs interest. UAVs are suited for a wide range of civilian and military applications; however, UAVs currently can not integrate with civilian airspace because of stringent safety requirements. Hence, it is necessary to push the envelope for UAVs design and control so that they can learn from nature and have more self-aware capabilities to improve safety and reliability. This dissertation addresses some challenges involved with flight controller learning based on real-time modeling of UAV. Plenty of UAV applications require different operational capabilities within a composite mission. These capabilities include landing and taking off using short runways, while being able to perform missions that require a high cruise speed i.e. tracking applications. A composite mission also requires the aircraft to be able to hover or operate with low cruise speeds for applications involving stationary moments. All of these different operational modes require a hybrid aircraft design that combines fixed wing aircraft capabilities and Vertical Take-Off and Landing (VTOL) aircraft capabilities. However, extensive resources required for hybrid aircraft design prohibited the discovery of different revolutionary designs. The work presented in this dissertation describes the development of a rapid modeling, prototyping and controller design platform of an unmanned quadrotor aircraft. Three main objectives are investigated: intelligent excitation input design, real-time parameter estimation, and learning control. Real-time estimation of dynamic model parameters is important for control adaptation. However, the aircraft model estimation performance can be severely degraded by an active control system and highly collinear model terms such as those found on a quadrotor unmanned aircraft. Recursive Fourier Transform Regression was applied to estimate parameters of different model forms/structures and using different excitation levels. The generated models are utilized to reconfigure a Nonlinear Dynamic Inversion (NDI) controller considering different testing conditions: normal, failure, and learning flights. Finally,an intelligent input design technique is proposed which enables autonomous identification of the vehicle’s response modal frequencies and emphasizes excitation power accordingly.Introduction -- Literature review -- Real-time closed loop system identification of a Quad-copter -- Flight controller learning based on real-time model estimation of a quadrotor aircraft -- Unmanned aircraft system intelligent system identification experiment design -- Conclusion and future work -- Appendix A. Power spectrum of a multisine signal -- Appendix B. Power spectrum of a multisine signa

Automatic control of a multirotor

Objective of this thesis is to describe the design and realisation phases of a multirotor to be used for low risk and cost aerial observation. Starting point of this activity was a wide literature study related to the technological evolution of multirotors design and to the state of the art. Firstly the most common multirotor configurations were defined and, according to a size and performance based evaluation, the most suitable one was chosen. A detailed computer aided design model was drawn as basis for the realisation of two prototypes. The realised multirotors were “X-shaped” octorotors with eight coaxially coupled motors. The mathematical model of the multirotor dynamics was studied. “Proportional Integral Derivative” and “Linear Quadratic” algorithms were chosen as techniques to regulate the attitude dynamics of the multirotor. These methods were tested with a nonlinear model simulation developed in the Matlab Simulink environment. In the meanwhile the Arduino board was selected as the best compromise between costs and performance and the above mentioned algorithms were implemented using this platform thanks to its main characteristic of being completely “open source”. Indeed the multirotor was conceived to be a serviceable tool for the public utility and, at the same time, to be an accessible device for research and studies. The behaviour of the physical multirotor was evaluated with a test bench designed to isolate the rotation about one single body axis at a time. The data of the experimental tests were gathered in real time using a custom Matlab code and several indoor tests allowed the “fine tuning” of the controllers gains. Afterwards a portable “ground station” was conceived and realised in adherence with the real scenarios users needs. Several outdoor experimental flights were executed with successful results and the data gathered during the outdoor tests were used to evaluate some key performance indicators as the endurance and the maximum allowable payload mass. Then the fault tolerance of the control system was evaluated simulating and experimenting the loss of one motor; even in this critical condition the system exhibited an acceptable behaviour. The reached project readiness allowed to meet some potential users as the “Turin Fire Department” and to cooperate with them in a simulated emergency. During this event the multirotor was used to gather and transmit real time aerial images for an improved “situation awareness”. Finally the study was extended to more innovative control techniques like the neural networks based ones. Simulations results demonstrated their effectiveness; nevertheless the inherent complexity and the unreliability outside the training ranges could have a catastrophic impact on the airworthiness. This is a factor that cannot be neglected especially in the applications related to flying platforms. Summarising, this research work was addressed mainly to the operating procedures for implementing automatic control algorithms to real platforms. All the design aspects, from the preliminary multirotor configuration choice to the tests in possible real scenarios, were covered obtaining performances comparable with other commercial of-the-shelf platforms

Proceedings of the International Micro Air Vehicles Conference and Flight Competition 2017 (IMAV 2017)

The IMAV 2017 conference has been held at ISAE-SUPAERO, Toulouse, France from Sept. 18 to Sept. 21, 2017. More than 250 participants coming from 30 different countries worldwide have presented their latest research activities in the field of drones. 38 papers have been presented during the conference including various topics such as Aerodynamics, Aeroacoustics, Propulsion, Autopilots, Sensors, Communication systems, Mission planning techniques, Artificial Intelligence, Human-machine cooperation as applied to drones

Modeling, identification and control of a quad-rotor drone using low-resolution sensing

This thesis focuses on the modeling and identification, control and filter design, simulation and animation, and experiments of an electrical-motor drive model-scale quadrotor --- the AR.Drone. Equations of Motion of drone’s model were derived from Kinemics and Dynamics of common quadrotors. The identification was conducted thoroughly including its low-resolution on-board sensors, such as rate gyro and altimeter. Control targets are composed of two stages --- local references following and global position tracking. PID algorithm is used by both controllers with various filters designs, such as low/high pass filter, Complementary Filter and Kalman Filter. Simulation is also divided to two stages with two different simulators ---- MATLAB and C++. The first stage MATLAB simulation is intended to only test the controllers with no disturbances or noises. The second stage high fidelity C++ simulation contains everything including animation. Experiments results are presented and correlated to simulation to evaluate the identification and modeling. This thesis also includes modeling and identification of a low-resolution camera sensor --- Kinect. The model is included in global position tracking simulation. Some experiments videos and animation videos are available at http://www.youtube.com/user/sunyue89/videos. The author hopes this thesis is helpful to researchers and amateurs who would like to develop the AR.Drone or any other small scale quadrotors using low-resolution sensing for autonomous control