Survey on Aerial Multirotor Design: a Taxonomy Based on Input Allocation

This paper reviews the impact of multirotor aerial vehicles designs on their abilities in terms of tasks and system properties. We propose a general taxonomy to characterize and describe multirotor aerial vehicles and their design, which we apply exhaustively on the vast literature available. Thanks to the systematic characterization of the designs we exhibit groups of designs having the same abilities in terms of achievable tasks and system properties. In particular, we organize the literature review based on the number of atomic actuation units and we discuss global properties arising from their choice and spatial distribution in the designs. Finally, we provide a discussion on the common traits of the designs found in the literature and the main future open problems

Trajectory optimization and motion planning for quadrotors in unstructured environments

Trajectory optimization and motion planning for quadrotors in unstructured environments Coming out from university labs robots perform tasks usually navigating through unstructured environment. The realization of autonomous motion in such type of environments poses a number of challenges compared to highly controlled laboratory spaces. In unstructured environments robots cannot rely on complete knowledge of their sorroundings and they have to continously acquire information for decision making. The challenges presented are a consequence of the high-dimensionality of the state-space and of the uncertainty introduced by modeling and perception. This is even more true for aerial-robots that has a complex nonlinear dynamics a can move freely in 3D-space. To avoid this complexity a robot have to select a small set of relevant features, reason on a reduced state space and plan trajectories on short-time horizon. This thesis is a contribution towards the autonomous navigation of aerial robots (quadrotors) in real-world unstructured scenarios. The first three chapters present a contribution towards an implementation of Receding Time Horizon Optimal Control. The optimization problem for a model based trajectory generation in environments with obstacles is set, using an approach based on variational calculus and modeling the robots in the SE(3) Lie Group of 3D space transformations. The fourth chapter explores the problem of using minimal information and sensing to generate motion towards a goal in an indoor bulding-like scenario. The fifth chapter investigate the problem of extracting visual features from the environment to control the motion in an indoor corridor-like scenario. The last chapter deals with the problem of spatial reasoning and motion planning using atomic proposition in a multi-robot environments with obstacles

Modeling and control of an overactuated aerial vehicle with four tiltable quadrotors attached by means of passive universal joints

We present a novel overactuated aerial vehicle based on four quadrotors connected to an airframe by means of passive universal joints. The proposed architecture allows to independently control the six degrees of freedom of the airframe without having fixed propellers at inefficient configurations or making use of dedicated rotor tilting actuators. After deriving the dynamic equations that describe its motion, we propose a linear control strategy that is able to successfully decouple rotation and translation, relying exclusively on on-board sensors. A prototype is built and preliminary experimental results demonstrate that the concept is feasible.Video: https://youtu.be/9ASP3FyhCJw.This research was supported by the ELKARTEK 2018 program of the Basque Government, grant agreement No. KK-2018/00082

Algoritmo bioinspirado a redes de robots para la asistencia en operaciones de busqueda y rescate

ilustraciones, diagramas, fotografíasThis thesis proposes a bio-inspired algorithm for robot networks assisting in the operations of search and rescue scenarios. We consider ants as social animals to study and abstract beha- viors that can be useful in the framework of search and rescue using robots. We consider three main topics to address when using robots to assist rescuers. First, the exploration and mapping of the disaster zones. For this, we consider the mecha- nisms and interactions of ants to explore their environment, look for food, avoid predators, and explore better places to establish a nest. Then, we deploy robots to explore the en- vironment and discourage robots from entering regions other robots have explored using pheromones as markers for the robots. We also abstract the randomness ants use to explore and implement a Q-learning algorithm that allows robots to explore unvisited regions. Second, the navigation and victim detection. Once the environment has been explored, we vi use Reynolds rules to allow the navigation of robots to create cohesion, attraction to target goals, and repulsion to obstacles and inter-agent collisions. Then, we use a neural network to determine whether what robots are detecting is a victim. Lastly, we use a consensus-like approach to classify victims or no victims based on distributed information. Lastly, ants have been famous for carrying loads that surpass their size and payload capacity by cooperating. We consider quadrotors to carry loads cooperatively that can be medical supplies or victims in search and rescue (Texto tomado de la fuente)Esta tesis propone un algoritmo bioinspirado para redes de robots que asisten en las operaciones de escenarios de busqueda y rescate. Consideramos a las hormigas como animales sociales para estudiar y abstraer comportamientos que pueden ser utiles en el marco de la busqueda y rescate mediante robots. Consideramos tres temas principales para abordar cuando se utilizan robots para ayudar a los rescatistas. Primero, la exploracion y mapeo de las zonas de desastre. Para esto, consideramos los mecanismos e interacciones de las hormigas para explorar su entorno, buscar comida, evitar depredadores y explorar mejores lugares para establecer un nido. Luego, desplegamos robots para explorar el entorno y disuadimos a los robots de ingresar a regiones que otros robots han explorado usando feromonas como marcadores para los robots. Tambien abstraemos la aleatoriedad que usan las hormigas para explorar e implementar un algoritmo Q-learning que permite a los robots explorar regiones no visitadas. En segundo lugar, la navegacion y deteccion de vıctimas. Una vez que se ha explorado el entorno, usamos las reglas de Reynolds para permitir que la navegacion de los robots cree cohesion, atraccion hacia los objetivos y repulsion hacia los obstaculos y las colisiones entre agentes. Luego, usamos una red neuronal para determinar si lo que detectan los robots es una vıctima. Por ultimo, utilizamos un enfoque de consenso para clasificar a las vıctimas o no vıctimas en funcion de la informacion distribuida. Por ultimo, las hormigas han sido famosas por llevar cargas que superan su tamano y capacidad de carga al cooperar. Consideramos quadrotors para transportar cargas de manera cooperativa que pueden ser suministros medicos o vıctimas en busqueda y rescate.MaestríaMagister en Ingenieria - Automatizacion IndustrialRobotic

Tracking Control of Quadrotors

In this thesis, the tracking control problem of a 6 DOF quadrotor is considered, and different control method is proposed considering optimal control, parametric and nonparametric uncertainty, input saturation, and distributed formation control. An optimal control approach is developed for single quadrotor tracking by minimizing the cost function. For uncertainties of the dynamic system, a robust adaptive tracking controller is proposed with the special structure of the dynamics of the system. Considering the uncertainty and input constraints, a robust adaptive saturation controller is proposed with the aid of an auxiliary compensated system. Decentralized formation control method for quadrotors is presented using a leader-follower scheme using proposed optimal control method. Virtual leader is employed to drive the quadrotors to their desired formation and ultimately track the trajectory defined by the virtual leader. Sliding mode estimators have been implemented to estimate the states of the virtual leader. The control method is designed considering switching communication topologies among the quadrotors. Simulation results are provided to show the effectiveness of the proposed approaches

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

Exploiting Heterogeneity in Networks of Aerial and Ground Robotic Agents

By taking advantage of complementary communication technologies, distinct sensing functionalities and varied motion dynamics present in a heterogeneous multi-robotic network, it is possible to accomplish a main mission objective by assigning specialized sub-tasks to specific members of a robotic team. An adequate selection of the team members and an effective coordination are some of the challenges to fully exploit the unique capabilities that these types of systems can offer. Motivated by real world applications, we focus on a multi-robotic network consisting off aerial and ground agents which has the potential to provide critical support to humans in complex settings. For instance, aerial robotic relays are capable of transporting small ground mobile sensors to expand the communication range and the situational awareness of first responders in hazardous environments. In the first part of this dissertation, we extend work on manipulation of cable-suspended loads using aerial robots by solving the problem of lifting the cable-suspended load from the ground before proceeding to transport it. Since the suspended load-quadrotor system experiences switching conditions during this critical maneuver, we define a hybrid system and show that it is differentially-flat. This property facilitates the design of a nonlinear controller which tracks a waypoint-based trajectory associated with the discrete states of the hybrid system. In addition, we address the case of unknown payload mass by combining a least-squares estimation method with the designed controller. Second, we focus on the coordination of a heterogeneous team formed by a group of ground mobile sensors and a flying communication router which is deployed to sense areas of interest in a cluttered environment. Using potential field methods, we propose a controller for the coordinated mobility of the team to guarantee inter-robot and obstacle collision avoidance as well as connectivity maintenance among the ground agents while the main goal of sensing is carried out. For the case of the aerial communications relays, we combine antenna diversity with reinforcement learning to dynamically re-locate these relays so that the received signal strength is maintained above a desired threshold. Motivated by the recent interest of combining radio frequency and optical wireless communications, we envision the implementation of an optical link between micro-scale aerial and ground robots. This type of link requires maintaining a sufficient relative transmitter-receiver position for reliable communications. In the third part of this thesis, we tackle this problem. Based on the link model, we define a connectivity cone where a minimum transmission rate is guaranteed. For example, the aerial robot has to track the ground vehicle to stay inside this cone. The control must be robust to noisy measurements. Thus, we use particle filters to obtain a better estimation of the receiver position and we design a control algorithm for the flying robot to enhance the transmission rate. Also, we consider the problem of pairing a ground sensor with an aerial vehicle, both equipped with a hybrid radio-frequency/optical wireless communication system. A challenge is positioning the flying robot within optical range when the sensor location is unknown. Thus, we take advantage of the hybrid communication scheme by developing a control strategy that uses the radio signal to guide the aerial platform to the ground sensor. Once the optical-based signal strength has achieved a certain threshold, the robot hovers within optical range. Finally, we investigate the problem of building an alliance of agents with different skills in order to satisfy the requirements imposed by a given task. We find this alliance, known also as a coalition, by using a bipartite graph in which edges represent the relation between agent capabilities and required resources for task execution. Using this graph, we build a coalition whose total capability resources can satisfy the task resource requirements. Also, we study the heterogeneity of the formed coalition to analyze how it is affected for instance by the amount of capability resources present in the agents

Kinodynamic motion planning for quadrotor-like aerial robots

Motion planning is the field of computer science that aims at developing algorithmic techniques allowing the automatic computation of trajecto- ries for a mechanical system. The nature of such a system vary according to the fields of application. In computer animation it could be a humanoid avatar. In molecular biology it could be a protein. The field of application of this work being aerial robotics, the system is here a four-rotor UAV (Unmanned Aerial Vehicle) called quadrotor. The motion planning problem consists in computing a series of motions that brings the system from a given initial configuration to a desired final configuration without generating collisions with its environment, most of the time known in advance. Usual methods explore the system’s configuration space regardless of its dynamics. By construction the thrust force that allows a quadrotor to fly is tangential to its attitude which implies that not every motion can be performed. Furthermore, the magnitude of this thrust force and hence the linear acceleration of the center of mass are limited by the physical capabilities of the robot. For all these reasons, not only position and orientation must be planned, higher derivatives must be planned also if the motion is to be executed. When this is the case we talk of kinodynamic motion planning. A distinction is made between the local planner and the global planner. The former is in charge of producing a valid trajectory between two states of the system without necessarily taking collisions into account. The later is the overall algorithmic process that is in charge of solving the motion planning problem by exploring the state space of the system. It relies on multiple calls to the local planner. We present a local planner that interpolates two states consisting of an arbitrary number of degrees of freedom (dof) and their first and second derivatives. Given a set of bounds on the dof derivatives up to the fourth order (snap), it quickly produces a near-optimal minimum time trajectory that respects those bounds. In most of modern global motion planning algorithms, the exploration is guided by a distance function (or metric). The best choice is the cost-to-go, i.e. the cost associated to the local method. In the context of kinodynamic motion planning, it is the duration of the minimal-time trajectory. The problem in this case is that computing the cost-to-go is as hard (and thus as costly) as computing the optimal trajectory itself. We present a metric that is a good approximation of the cost-to-go but which computation is far less time consuming. The dominant paradigm nowadays is sampling-based motion planning. This class of algorithms relies on random sampling of the state space in order to quickly explore it. A common strategy is uniform sampling. It however appears that, in our context, it is a rather poor choice. Indeed, a great majority of uniformly sampled states cannot be interpolated. We present an incremental sampling strategy that significantly decreases the probability of this happening

An Omnidirectional Aerial Platform for Multi-Robot Manipulation

The objectives of this work were the modeling, control and prototyping of a new fully-actuated aerial platform. Commonly, the multirotor aerial platforms are under-actuated vehicles, since the total propellers thrust can not be directed in every direction without inferring a vehicle body rotation. The most common fully-actuated aerial platforms have tilted or tilting rotors that amplify the aerodynamic perturbations between the propellers, reducing the efficiency and the provided thrust. In order to overcome this limitation a novel platform, the ODQuad (OmniDirectional Quadrotor), has been proposed, which is composed by three main parts, the platform, the mobile and rotor frames, that are linked by means of two rotational joints, namely the roll and pitch joints. The ODQuad is able to orient the total thrust by moving only the propellers frame by means of the roll and pitch joints. Kinematic and dynamic models of the proposed multirotor have been derived using the Euler- Lagrange approach and a model-based controller has been designed. The latter is based on two control loops: an outer loop for vehicle position control and an inner one for vehicle orientation and roll-pitch joint control. The effectiveness of the controller has been tested by means of numerical simulations in the MATLAB c SimMechanics environment. In particular, tests in free motion and in object transportation tasks have been carried out. In the transportation task simulation, a momentum based observer is used to estimate the wrenches exchanged between the vehicle and the transported object. The ODQuad concept has been tested also in cooperative manipulation tasks. To this aim, a simulation model was considered, in which multiple ODQuads perform the manipulation of a bulky object with unknown inertial parameters which are identified in the first phase of the simulation. In order to reduce the mechanical stresses due to the manipulation and enhance the system robustness to the environment interactions, two admittance filters have been implemented: an external filter on the object motion and an internal one local for each multirotor. Finally, the prototyping process has been illustrated step by step. In particular, three CAD models have been designed. The ODQuad.01 has been used in the simulations and in a preliminary static analysis that investigated the torque values for a rough sizing of the roll-pitch joint actuators. Since in the ODQuad.01 the components specifications and the related manufacturing techniques have not been taken into account, a successive model, the ODQuad.02, has been designed. The ODQuad.02 design can be developed with aluminum or carbon fiber profiles and 3D printed parts, but each component must be custom manufactured. Finally, in order to shorten the prototype development time, the ODQuad.03 has been created, which includes some components of the off-the-shelf quadrotor Holybro X500 into a novel custom-built mechanical frame

Bearing-only Formation Control of multiple UAVs with an NMPC approach: architectures and methodologies

openUno dei maggior campi di sviluppo e d’innovazione nel nostro secolo riguarda l’ambito della robotica mobile in particolare lo studio del coordinamento di sistemi multi agenti. Questo tipo di tecnologia permette di essere impiegata in ambiti di calamità naturali o situazioni critiche dove i sistemi multi agenti posso operare missioni di search and rescue o monitoraggio ambientale. In campo vengono impiegati veicoli terrestri autonomi UGV (Unmanned Ground Vehicle) e veicoli aerei autonomi UAV(Unmanned Aerial Vehicle) che possono cooperare tra di loro. Gli ambienti esterni presentano diverse problematiche e una di queste può essere la mancanza di accesso alla rete GPS. Per tale motivo si studiano leggi di controllo che non impiegano questo tipo di informazioni come bearing-only formation control dove gli agenti rilevano tra di loro solo angoli relativi, i quali possono essere calcolati tramite una semplice camera 2D. Questo lavoro di tesi ha lo scopo di esplorare la teoria della bearing rigidity applicata a formazioni di agenti omogenei nello specifico quadricotteri sfruttando la tecnologia NMPC con MATMPC. La tesi va ad esplorare le differenze delle diverse architetture in particolare va ad implementare una architettura centralizzata e mette giù le basi per un possibile sviluppo di un’architettura decentralizzata. Il lavoro mostra come è creare il modello per NMPC con diverse varianti del modello dell’agente (come è stato modellizzato), diversi funzionali di costo e diverse formazioni. Per l’implementazione viene usato ROS2 per lo sviluppo dell’intero ecosistema di controllo e viene usata la piattaforma PX4 che mette a disposizione un ottima architettura di controllo a basso livello per la gestione del singolo quadricottero. Inoltre la tesi usa il sistema SITL(Software In The Loop) di PX4 per rendere le simulazioni di Gazebo il più vicine alla realtà.One of the major fields of development and innovation in our century concerns mobile robotics, particularly the study of multi-agent system coordination. This type of technol- ogy can be employed in natural disaster scenarios or critical situations where multi-agent systems can perform search and rescue missions or environmental monitoring. In this field, autonomous ground vehicles (UGVs) and unmanned aerial vehicles (UAVs) are used, which can cooperate with each other. Outdoor environments pose various challenges, and one of these challenges can be the lack of access to GPS network. For this reason, control laws that do not rely on GPS information are studied, such as ”bearing-only formation control,” where agents only perceive relative angles between each other, which can be calculated using a simple 2D camera. The purpose of this thesis work is to explore the theory of bearing rigidity applied to forma- tions of homogeneous agents, specifically quadcopters, using Nonlinear Model Predictive Control (NMPC) with MATMPC. The thesis aims to explore the differences between dif- ferent architectures, particularly by implementing a centralized architecture and laying the groundwork for a possible development of a decentralized architecture. The work demon- strates how to create the model for NMPC with various agent model variants,different cost functions, and different formations. ROS2 is used for the implementation of the entire control ecosystem, and the PX4 platform is used, which provides an excellent low-level control architecture for managing individual quadcopters. Additionally, the thesis utilizes the PX4 Software In The Loop (SITL) system to make Gazebo simulations as close to reality as possible