<p>This thesis consists of four independent papers concerningthe control of mobile robots in the context of obstacleavoidance and formation keeping.</p><p>The first paper describes a new theoreticallyv erifiableapproach to obstacle avoidance. It merges the ideas of twoprevious methods, with complementaryprop erties, byusing acombined control Lyapunov function (CLF) and model predictivecontrol (MPC) framework.</p><p>The second paper investigates the problem of moving a fixedformation of vehicles through a partiallykno wn environmentwith obstacles. Using an input to state (ISS) formulation theconcept of configuration space obstacles is generalized toleader follower formations. This generalization then makes itpossible to convert the problem into a standard single vehicleobstacle avoidance problem, such as the one considered in thefirst paper. The properties of goal convergence and safetyth uscarries over to the formation obstacle avoidance case.</p><p>In the third paper, coordination along trajectories of anonhomogenuos set of vehicles is considered. Byusing a controlLyapunov function approach, properties such as boundedformation error and finite completion time is shown.</p><p>Finally, the fourth paper applies a generalized version ofthe control in the third paper to translate,rotate and expanda formation. It is furthermore shown how a partial decouplingof formation keeping and formation mission can be achieved. Theapproach is then applied to a scenario of underwater vehiclesclimbing gradients in search for specific thermal/biologicalregions of interest. The sensor data fusion problem fordifferent formation configurations is investigated and anoptimal formation geometryis proposed.</p><p><b>Keywords:</b>Mobile Robots, Robot Control, ObstacleAvoidance, Multirobot System, Formation Control, NavigationFunction, Lyapunov Function, Model Predictive Control, RecedingHorizon Control, Gradient Climbing, Gradient Estimation.</p>

Cooperative control enables combinations of sensor data from multiple autonomous underwater vehicles (AUVs) so that multiple AUVs can perform smarter behaviors than a single AUV. In addition, in some situations, a human-driven underwater vehicle (HUV) and a group of AUVs need to collaborate and preform formation behaviors. However, the collective dynamics of a fleet of heterogeneous underwater vehicles are more complex than the non-trivial single vehicle dynamics, resulting in challenges in analyzing the formation behaviors of a fleet of heterogeneous underwater vehicles. The research addressed in this dissertation investigates the collective dynamics and control of a fleet of heterogeneous underwater vehicles, including multi-AUV systems and systems comprised of an HUV and a group of AUVs (human-AUV systems). This investigation requires a mathematical motion model of an underwater vehicle. This dissertation presents a review of a six-degree-of-freedom (6DOF) motion model of a single AUV and proposes a method of identifying all parameters in the model based on computational fluid dynamics (CFD) calculations. Using the method, we build a 6DOF model of the EcoMapper and validate the model by field experiments. Based upon a generic 6DOF AUV model, we study the collective dynamics of a multi-AUV system and develop a method of decomposing the collective dynamics. After the collective dynamics decomposition, we propose a method of achieving orientation control for each AUV and formation control for the multi-AUV system. We extend the results and propose a cooperative control for a human-AUV system so that an HUV and a group of AUVs will form a desired formation while moving along a desired trajectory as a team. For the post-mission stage, we present a method of analyzing AUV survey data and apply this method to AUV measurement data collected from our field experiments carried out in Grand Isle, Louisiana in 2011, where AUVs were used to survey a lagoon, acquire bathymetric data, and measure the concentration of reminiscent crude oil in the water of the lagoon after the BP Deepwater Horizon oil spill in the Gulf of Mexico in 2010.

Multi-vehicle systems offer many advantages in engineering applications such as increased efficiency and robustness. However, the disadvantage of multi-vehicle systems is that they require a high level of organization and coordination in order to successfully complete a task. Formation control is a field of engineering that addresses this issue, and provides coordination schemes to successfully implement multi-vehicle systems. Two approaches to group coordination were proposed in this work: geometric and self-organizing formations. A geometric reconfiguring formation was developed using the leader-follower method, and the self-organizing formation was developed using the velocity potential equations from fluid flow theory. Both formation controllers were first tested in simulation in MATLAB, and then implemented on the X80 mobile robot units. Various experiments were conducted to test the formations under difficult obstacle scenarios. The robots successfully navigated through the obstacles as a coordinated as a team using the self-organizing and geometric formation control approaches.

This thesis consists of four independent papers concerningthe control of mobile robots in the context of obstacleavoidance and formation keeping. The first paper describes a new theoreticallyv erifiableapproach to obstacle avoidance. It merges the ideas of twoprevious methods, with complementaryprop erties, byusing acombined control Lyapunov function (CLF) and model predictivecontrol (MPC) framework. The second paper investigates the problem of moving a fixedformation of vehicles through a partiallykno wn environmentwith obstacles. Using an input to state (ISS) formulation theconcept of configuration space obstacles is generalized toleader follower formations. This generalization then makes itpossible to convert the problem into a standard single vehicleobstacle avoidance problem, such as the one considered in thefirst paper. The properties of goal convergence and safetyth uscarries over to the formation obstacle avoidance case. In the third paper, coordination along trajectories of anonhomogenuos set of vehicles is considered. Byusing a controlLyapunov function approach, properties such as boundedformation error and finite completion time is shown. Finally, the fourth paper applies a generalized version ofthe control in the third paper to translate,rotate and expanda formation. It is furthermore shown how a partial decouplingof formation keeping and formation mission can be achieved. Theapproach is then applied to a scenario of underwater vehiclesclimbing gradients in search for specific thermal/biologicalregions of interest. The sensor data fusion problem fordifferent formation configurations is investigated and anoptimal formation geometryis proposed. Keywords:Mobile Robots, Robot Control, ObstacleAvoidance, Multirobot System, Formation Control, NavigationFunction, Lyapunov Function, Model Predictive Control, RecedingHorizon Control, Gradient Climbing, Gradient Estimation. / QC 20111121

Cette thèse propose des solutions aux problématiques inhérentes au contrôle de formations aériennes de type leader­-suiveur pour des flottes de quadrirotors. Au regard des travaux existants, les stratégies qui sont proposés dans notre travail, considère que le(s) leader{s) a une interaction avec les suiveurs. En outre, les rôles de leader et de suiveur sont interchangeables lors de la formation. Dans un premier temps, la modélisation mathématique d'un seul quadrirotor et celle de la formation de quadrirotors est développée. Ensuite, le problème de suivi de trajectoire pour un seul quadrirotor est étudié. Au travers de l'analyse de 1, dynamique du système pour la conception d'une commande par platitude, il apparait que le suivi de trajectoire pour chaque quadrirotor équivaut à déterminer les sorties plates désirées. Un contrôleur pour système plats permettant l'asservissement des drones pour le suivi de trajectoire est donc proposé. Étant donné la propriété de double-boucle de la dynamique du quadrirotor en boucle fermée, un contrôleur d'attitude avec des grands gains est conçu, selon la théorie « singular perturbation system ». Puisque la dynamique du quadrirotor en boucle fermée fonctionne sur deux échelles de temps, la dynamique de rotation (boundary-layer mode) est contrôlée sur l'échelle de temps la plus rapide. La conception du contrôleur de formation dépend seulement de la dynamique de translation (modèle réduit dans une échelle de temps lente). Ce résultat a simplifié la conception du contrôleur de formation, de telle sorte que le modèle réduit du quadrirotor est utilisé au lieu du modèle complet. Étant donné que le modèle réduit du quadrirotor a une caractéristique de double-intégrateur, un algorithme de consensus pour des systèmes caractérisés par de multiple double-intégrateurs est proposé. Pour traiter le problème de la formation leader-suiveur, une matrice d'interaction est initialement proposée basée sur la matrice de Laplacienne. Nous montrons que la condition de convergence et la vitesse de convergence de l'erreur de formation dépendent de la plus petite valeur propre de la matrice d'interaction. Trois stratégies de contrôle de la formation avec une topologie fixe sont ensuite proposées. Le contrôle de formation par platitude est proposé pour obtenir une formation agressive, tandis que les dérivées de grands ordres de la trajectoire désirée pour chaque UAV sont estimées en utilisant un observateur; la méthode Lyapunov redesign est implémentée pour traiter les non-linéarités de la dynamique de la translation des quadrotors; une loi de commande bornée par l'utilisation, entre autre, de la fonction tangente hyperbolique est développée avec un feedback composite non linéaire, afin d'améliorer les performances de la formation. De plus, une commande de commutation saturée de la formation est étudiée, car la topologie de la formation est variable. La stabilité du système est obtenue grâce aux théories “convex hull » et « common Lyapunov function ». Cette stratégie de commande de commutation permet le changement des leaders dans la formation. Inspirée par certains travaux existants, tels que le contrôle de la formation avec des voisins anonymes, nous proposons, finalement, une loi de commande avec des voisins pondérés, qui montre une meilleure robustesse que le contrôle avec des voisins anonymes. Les résultats de simulation obtenus avec Matlab illustrent premièrement nos stratégies de contrôle que nous proposons De plus, en utilisant le langage de programmation C ++, nos stratégies sont mises en œuvre dans un framework de simulation et d'expérimentation développé au laboratoire Heudiasyc. Grâce aux nombreux tests variés que nous avons réalisés en simulation et en temps-réel, l'efficacité et les avantages de nos stratégies de contrôle de la formation proposées sont présentés. / In this thesis, we address a leader-follower (L-F) formation control problem for multiple UAVs, especially quadrotors. Different from existing works, the strategies, which are proposed in our work, consider that the leader(s) have interaction with the followers. Additionally, the leader(s) are changeable during the formation. First, the mathematical modeling of a single quadrotor and of the formation of quadrotors is developed. The trajectory tracking problem for a single quadrotor is investigated. Through the analysis of the flatness of the quadrotor dynamical model, the desired trajectory for each quadrotor is transferred to the design of the desired at outputs. A flatness-based trajectory tracking controller is, then, proposed. Considering the double-loop property of the closed-loop quadrotor dynamics, a high-gain attitude controller is designed, according to the singular perturbation system theory. Since the closed-loop quadrotor dynamics performs in two time scales, the rotational dynamics (boundary-layer model) is controlled in a fast time scale. The formation controller design is then only considered for the translational dynamics: reduced model in a slow time scale. This result has simplified the formation controller design such that the reduced model of the quadrotor is considered instead of the complete model. Since the reduced model of the quadrotor has a double-integrator characteristic, consensus algorithm for multiple double-integrator systems is proposed. Dealing with the leader-follower formation problem, an interaction matrix is originally proposed based on the Laplacian matrix. We prove that the convergence condition and convergence speed of the formation error are in terms of the smallest eigenvalue of the interaction matrix. Three formation control strategies with fixed formation topology are then proposed. The flatness-based formation control is proposed to deal with the aggressive formation problem, while the high-order derivatives of the desired trajectory for each UAV are estimated by using an observer; the Lyapunov redesign is developed to deal with the nonlinearities of the translational dynamics of the quadrotors; the hyperbolic tangent-based bounded control with composite nonlinear feedback is developed in order to improve the performance of the formation. In an additional way, a saturated switching control of the formation is investigated, where the formation topology is switching. The stability of the system is obtained by introducing the convex hull theory and the common Lyapunov function. This switching control strategy permits the change of the leaders in the formation. Inspired by some existing works, such as the anonymous neighbor-based formation control, we finally propose a weighted neighbor-based control, which shows better robustness than the anonymous neighbor-based control. Simulation results using Matlab primarily illustrate our proposed formation control strategies. Furthermore, using C++ programming, our strategies are implemented on the simulator-experiment framework, developed at Heudiasyc laboratory. Through a variety of tests on the simulator and real-time experiments, the efficiency and the advantages of our proposed formation control strategies are shown. Finally, a vision-based inter-distance detection system is developed. This system is composed by an on-board camera, infrared LEDs and an infrared filter. The idea is to detect the UAVs and calculate the inter-distance by calculating the area of the special LEDs patterns. This algorithm is validated on a PC, with a webcam and primarily implemented on a real quadrotor.

Este trabalho trata da coordenação de robôs heterogêneos que consiste em um robô helicóptero e em múltiplos robôs móveis com rodas, de modo que estes sigam um líder. Para atingirmos este objetivo, neste trabalho desenvolve-se a estimação da atitude e posição de um robô utilizando filtros robustos. Os filros realizam a fusão dos sinais de uma unidade de medida inercial de baixo custo e de um receptor GPS (Global Positioning System) considerando um modelo de corpo rígido formulado em termos de quatérnios. Resultados experimentais são apresentados baseados em um estudo comparativo entre os filtros robustos e o filtro de Kalman. Desenvolve-se o controle de um robô móvel com rodas deslizantes e de um robô helicóptero. Para realizar o controle robusto utilzia-se um regulador robusto recursivo. Simulaçõoes do robô móvel com rodas deslizantes e do robô helicóptero são apresentadas utilizando os parâmetros de um robô móvel Pioneer 3AT e de um robô helicóptero RMAX. Desenvolve-se também um mini robô helicóptero e uma base de movimento para realização de testes de controle do mini robô helicóptero constiste de um mini helimodelo e de um piloto automático baseado em um microprocessador com conectividade Wi-Fi, uma unidade de medida inercial e uma placa de controle de servos motores. E por fim, desenvolve-se a coordenação de robôs heterogêneos de modo que estes sigam um líder. Para isto é utilziado um controlador descentralizado e cooperativo cuja finalidade é gerar trajetórias de referência para que os robôs heterogênos se movimentem em formação rígida. / This research deals with the coordination of the heterogeneous robots, consisting of a robotic helicopter and multiple uheeled mobile robots, to achieve this aim this work develops the estimation of attitude, heading and positions of a robot based on robust filters. The filters perform the fusion of the signals of a low-cost inertial measurement unit and a GPS (Global Positioning System) receiver considering a rigid body model formulated in terms of quaternions. Experimental results are presented based on a comparative study of the robust filters and Kalman filter. It develops a robust control scheme of a ski-steering mobile robot and a robotic helicopter. The robust control is performed through a the robust recursive regulator. Simulations of the skid-steering mobile robot and a robotic helicopter are presented using the parameters of a Pioneer 3AT and a robotic helicopter RMAX. It also develops a mini robotic helicopter and a motion base to perform control test of a mini robotic helicopter. The mini robotic helicopter consists of a mini helicopter TREX 450 XL and an autopilot based on a microprocessor with Wi-Fi, an inertial measurement unit a servo control board. To finish, it develops the coordination of the heterogeneous robots in order to perform a leader strategy based on the concept of rigid formation.

Cette thèse présente l’étude d’une stratégie de coordination hybride d’un groupe de robots sous-marins pour la recherche d’objets de petites dimensions ou de singularités sur les fonds marins. Chaque robot est équipé d’un module de perception utilisant la librairie de traitement d’image OpenCV qui lui permet d’apercevoir les autres éléments de la meute ainsi que l’environnement d’évolution de la mission.Cette stratégie hybride est constituée de deux phases : une phase de mise en formation géométrique et une phase d’acquisition des données vidéo. La première phase s’appuie sur des algorithmes de type "essaims" alors que la seconde se fonde sur une méthode hiérarchique de coordination. En cas de perte de la formation, le groupe de robots quitte le mode hiérarchique et reprend le mode essaim pour se reformer. Ces changements de modes sont contrôlés par une machine à états finis. Avant d’entamer une expérimentation en grandeur nature, la méthodologie et les algorithmes de coordination doivent être testés et validés par simulation.Dans ce contexte, un simulateur basé sur le logiciel Blender a été conçu de façon à ce qu’il tienne compte des différentes contraintes liées à l’évolution des robots dans l’environnement sous-marin. Les résultats de simulation d’une meute de 3 AUVs montrent la capacité de notre stratégie à optimiser l’exécution d’une mission d’acquisition vidéo par un groupe de robots autonomes contrôlés par la vision et coordonnés par une stratégie hybride. / In the underwater environment, the needs of data acquisition have significantly increased over the last decades. As electromagnetic waves show poor propagation in sea water, acoustical sensing is generally preferred. However, the emergence of small and low cost autonomous underwater vehicles (AUV) allow for rethinking the underwater use of optical sensors as their small coverage can be significantly improved by using a fleet of coordinated underwater robots.This paper presents a strategy to coordinate the group of robots in order to systematically survey the seabed to detect small objects or singularities. The proposed hybrid coordination strategy is defined by two main modes. The first mode relies on a swarm algorithm to organize the team in geometrical formation. In the second mode, the robot formation is maintained using a hierarchical coordination. A finite state machine controls the high level hybrid strategy by defining the appropriate coordination mode according to the evolution of the mission. Before sea validation, the behavior and the performance of the hybrid coordination strategy are first assessed in simulation. The control of individual robots relies on visual servoing, implemented with the OpenCV library, and the simulation tool is based on Blender software.The dynamics of the robots has been implemented in a realistic way in Blender by using the Bullet solver and the hydrodynamic coeficcients estimated on the actual robot. First results of the hybrid coordination strategy applied on a fleet of 3 AUV’s, show execution of a video acquisition task by a group of autonomous robots controlled by vision and coordinated by a hybrid strategy.

Multi-vehicle systems offer many advantages in engineering applications such as increased efficiency and robustness. However, the disadvantage of multi-vehicle systems is that they require a high level of organization and coordination in order to successfully complete a task. Formation control is a field of engineering that addresses this issue, and provides coordination schemes to successfully implement multi-vehicle systems. Two approaches to group coordination were proposed in this work: geometric and self-organizing formations. A geometric reconfiguring formation was developed using the leader-follower method, and the self-organizing formation was developed using the velocity potential equations from fluid flow theory. Both formation controllers were first tested in simulation in MATLAB, and then implemented on the X80 mobile robot units. Various experiments were conducted to test the formations under difficult obstacle scenarios. The robots successfully navigated through the obstacles as a coordinated as a team using the self-organizing and geometric formation control approaches.

Autonomous robots have the potential to accomplisha wide variety of assignments. For this to work in reality, therobots need to be able to perform specific tasks while safety forboth them and their environment is ensured. Signal temporallogic (STL) was used to define timed tasks for the agents toperform and control barrier functions (CBFs) were used to designa controller for their movements. In this paper, a set of STL taskswere considered, which two robots were instructed to satisfy in asimulation of a warehouse environment. The two agents startednext to each other, then the set of tasks instructed them to move totwo separate areas, then meet up again and move in a formationback towards their starting area. Control barrier functions wereemployed to ensure the satisfaction of the set of STL tasks.The agents designed their actions towards satisfying the giventasks without considering a safety distance to the other robot atfirst. To later ensure safety, a collision avoidance mechanism wasintroduced. The scenario without collision avoidance proved moreeffective paths for the agents. They moved to satisfy the tasks withless disturbance than the scenario where collision avoidance wasconsidered. However, the scenario with the collision avoidancemechanism proved successful and the agents satisfied their taskswithout colliding with each other. / Autonoma robotar har potential att utföra en stor mängd olika uppgifter. För att detta ska fungera i verkligheten, behöver robotarna kunna genomföra specifika uppgifter medans både deras egen och omgivningens säkerhet är säkerställd. Signal temporal logic (STL) användes för att definiera tidsinställda uppgifter åt robotarna att utföra och control barrier functions (CBFs) användes för att designa en controller för deras rörelser. I den här rapporten betraktades en uppsättning av STL-uppgifter, vilka två robotar instruerades att uppfylla i en simulering av en lagermiljö. De två robotarna startade bredvid varandra, sen instruerade STL-uppgifterna dem att röra sig till två separata områden, sen mötas upp igen och röra sig i formation tillbaka mot sitt startområde. Control barrier functions användes för att garantera uppfyllandet av STL-uppgifterna. Robotarna anpassade sina rörelser till att uppfylla de givna uppgifterna, först utan hänsyn till någon säkerhetsmarginal till den andra roboten. För att senare garantera säkerhet introducerades en extra mekanism för att undvika kollision. Scenariot utan att undvika kollision visade på effektivare rörelsebanor hos robotarna. De rörde sig mot att uppfylla uppgifterna med färre störningar än scenariot då kollision aktivt undveks. Scenariot med mekanismen för att dock framgångsrikt och robotarna e sina uppgifter utan att kollidera med varandra. / Kandidatexjobb i elektroteknik 2021, KTH, Stockholm

<p dir="ltr">Unmanned surface vehicles (USVs) offer a versatile platform for various maritime applications, including research, surveillance, and search-and-rescue operations. A critical capability for USVs is maintaining position (station keeping) in dynamic environments and coordinating movement with other USVs (formation control) for collaborative missions. This thesis investigates control strategies for USVs operating in challenging conditions. </p><p dir="ltr">The initial focus is on evaluating traditional control methods like Backstepping and Sliding Mode controllers for station keeping in simulated environments with disturbances. The results from these tests pointed towards the need for a more robust control technique, like deep-learning based control for enhanced performance. </p><p dir="ltr">The thesis then explores formation control, a crucial aspect of cooperative USV missions. A vision-based passive control strategy utilizing a virtual leader concept is proposed. This approach leverages onboard cameras to detect markers on other USVs, eliminating the need for direct communication and potentially improving scalability and resilience. </p><p dir="ltr">Then the thesis presents vision-based formation control architecture and the station keeping controller evaluations. Simulation results are presented, analyzed, and used to draw conclusions about the effectiveness of the proposed approaches. Finally, the thesis discusses the implications of the findings and proposes potential future research directions</p>