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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">As traffic in cislunar space grows and missions become increasingly complex, effective understanding of relative motion between spacecraft is paramount. Additional tools are necessary to more accurately determine favorable relative behaviors in a multi-body gravitational environment. In this investigation, relative states are characterized as linear combinations of principal stretching and restoring directions to introduce techniques for relative trajectory design in the circular restricted three-body problem. These dynamically-informed directions form sets of orthonormal vector bases employed to describe and design spacecraft motion relative to a reference trajectory. Properties unique to 3x3 subsets of the state transition matrix are exploited to derive methodologies for two relative motion applications. First, the formulation is presented from a spacecraft loitering perspective, providing a framework to methodically determine ballistic relative trajectory options for visiting spacecraft. Secondly, modifications are introduced for flexible maneuver planning in a collision avoidance scenario. The two methodologies are assessed for a variety of test cases along four different periodic orbits in the Earth-Moon system.</p>

<p dir="ltr">Runway incursions remain a persistent safety risk affecting both towered and nontowered airports. While new technologies and initiatives are continuously discussed and developed, high costs and complexities of implementation remain barriers to adoption. Low-cost runway status lights, enabled by new surveillance methods and simplified lighting systems, may bring an effective method of providing direct-to-pilot warnings of runway conflicts to the nontowered and general aviation airports that need them most. Using a flight simulator in a virtual reality environment, the author presented three different scenarios with and without simplified runway entrance lights to pilots, comparing performance within subjects, while assessing the effect of providing system information to participants between subjects. An adapted NASA Task Load Index and post-participation survey were used to answer additional questions regarding pilot perceptions of the runway entrance lights. This study found that simplified runway entrance lights reduce the risk of runway incursions in nontowered, no-traffic environments when a conflicting aircraft is difficult to see. These findings were consistent with participants’ general opinion on the benefit of runway entrance lights. Furthermore, the provision of system information was found to be important but not critical to system effectiveness. Studies on pilot trust and other components of the runway status light system are recommended, as are real-world trials.</p>

Automobile accidents are one of the leading causes of death and claim more than 40,000 lives annually in the US alone. A substantial portion of these accidents occur at road intersections. Stop signs and traffic signals are some of the intersection control devices used to increase safety and prevent collisions. However, these devices themselves can contribute to collisions, are costly, inefficient, and are prone to failure. This thesis proposes an adaptive, decentralized, cooperative collision avoidance (CCA) system that optimizes each vehicle's controls subject to the constraint that no collisions occur. Three major contributions to the field of collision avoidance have resulted from this research. First, a nonlinear 5-state variable vehicle model is expanded from an earlier model developed in [1]. The model accounts for internal engine characteristics and more realistically approximates vehicle behavior in comparison to idealized, linear models. Second, a set of constrained, coupled Extended Kalman Filters (EKF) are used to predict the trajectory of the vehicles approaching an intersection in real-time. The coupled filters support decentralized operation and ensure that the optimization algorithm bases its decisions on good, reliable estimates. Third, a vehicular network based on the new WAVE standard is presented that provides cooperative capabilities by enabling intervehicle communication. The system is simulated against today's common intersection control devices and is shown to be superior in minimizing average vehicle delay. / Master of Science

This thesis presents the initial components of an integrated guidance, navigation, and control system for vertical take-off and landing (VTOL) autonomous unmanned aerial vehicles (UAVs) such that they may map complex environments that may be hostile. The first part of this thesis presents an autonomous guidance system. For goal selection, the map is partitioned around the presence of obstacles and whether that area has been explored. To perform this partitioning, the Octree algorithm is implemented. In this thesis, we test this algorithm to find a parameter set that optimizes this algorithm. Having selected goal points, we perform a comparison of the LPA* and A* path planning algorithms with a custom heuristic that enables reckless or tactical maneuvers as the UAV maps the environment. For trajectory planning, the fMPC algorithm is applied to the feedback-linearized equations of motion of a quadcopter. For collision avoidance, standalone versions of 4 different constraint generation algorithms are evaluated to compare their resulting computation times, accuracy, and computed volume on a voxel map that simulates a 2-story house along with fixed paths that vary in length at fixed intervals as basis of tests. The second part of this thesis presents the theory of Model Reference Adaptive Control(MRAC) along with augmentation for output signal tracking and switched-dynamic systems. We then detail the development of longitudinal and lateral controllers a Quad-Rotor Tailsitter(QRBP) style UAV. In order to successfully implement the proposed controller on the QRBP, significant effort was placed upon physical design and testing apparatus. / Master of Science / For an autonomously operated, Unmanned Aerial Vehicle (UAV), to operate, it requires a guidance system to determine where and how to go, and a control system to effectively actuate the guidance system's commands. In this thesis, we detail the characterization and optimization of the algorithms comprising the guidance system. We then delve into the theory of MRAC and apply it toward a control system for a QRBP. We then detail additional tools developed to support the testing of the QRBP.

Dans cette thèse, nous nous intéressons au système d’identification automatique spatial lequel est dédié à la surveillancemaritime par satellite. Ce système couvre une zone bien plus large que le système standard à terre correspondant àplusieurs cellules traditionnelles ce qui peut entraîner des risques de collision des données envoyées par des navireslocalisés dans des cellules différentes et reçues au niveau de l’antenne du satellite. Nous présentons différentes approchesafin de répondre au problème de collision considéré. Elles ne reposent pas toujours sur les mêmes hypothèses en ce quiconcerne les signaux reçus, et ne s’appliquent donc pas toutes dans les mêmes contextes (nombre de capteurs utilisés,mode semi-supervisé avec utilisation de trames d’apprentissage et information a priori ou mode aveugle, problèmes liés àla synchronisation des signaux, etc...).Dans un premier temps, nous proposons des méthodes permettant la séparation/dé-collision des messages en modèle surdéterminé(plus de capteurs que de messages). Elles sont fondées sur des algorithmes de décompositions matriciellesconjointes combinés à des détecteurs de points temps-fréquence (retard-fréquence Doppler) particuliers permettant laconstruction d’ensembles de matrices devant être (bloc) ou zéro (bloc) diagonalisées conjointement. En ce qui concerneles algorithmes de décompositions matricielles conjointes, nous proposons quatre nouveaux algorithmes de blocdiagonalisation conjointe (de même que leur version à pas optimal) fondés respectivement sur des algorithmesd’optimisation de type gradient conjugué, gradient conjugué pré-conditionné, Levenberg-Marquardt et Quasi-Newton. Lecalcul exact du gradient matriciel complexe et des matrices Hessiennes complexes est mené. Nous introduisonségalement un nouveau problème dénommé zéro-bloc diagonalisation conjointe non-unitaire lequel généralise le problèmedésormais classique de la zéro-diagonalisation conjointe non-unitaire. Il implique le choix d’une fonction de coût adaptéeet à nouveau le calcul de quantités telles que gradient matriciel complexe et les matrices Hessiennes complexes. Nousproposons ensuite trois nouveaux algorithmes à pas optimal fondés sur des algorithmes d’optimisation de type gradientconjugué, gradient conjugué pré-conditionné et Levenberg-Marquardt.Finalement, nous terminons par des approches à base de techniques de détection multi-utilisateurs conjointe susceptiblesde fonctionner en contexte sous-déterminé dans lequel nous ne disposons plus que d’un seul capteur recevantsimultanément plusieurs signaux sources. Nous commençons par développer une première approche par déflationconsistant à supprimer successivement les interférences. Nous proposons ensuite un deuxième mode opératoire fondéquant à lui sur l’estimateur du maximum de vraisemblance conjoint qui est une variante de l’algorithme de VITERBI. / This PHD thesis concerns the spatial automatic identification system dedicated to marine surveillance by satellite. Thissystem covers a larger area than the traditional system corresponding to several satellite cells. In such a system, there arerisks of collision of the messages sent by vessels located in different cells and received at the antenna of the samesatellite. We present different approaches to address the considered problem. They are not always based on the sameassumptions regarding the received signals and are not all applied in the same contexts (they depend on the number ofused sensors, semi-supervised mode with use of training sequences and a priori information versus blind mode, problemswith synchronization of signals, etc.). Firstly, we develop several approaches for the source separation/de-collision in theover-determined case (more sensors than messages) using joint matrix decomposition algorithms combined withdetectors of particular time-frequency (delay-Doppler frequency) points to build matrix sets to be joint (block) or zero(block) diagonalized. Concerning joint matrix decomposition algorithms, four new joint block-diagonalization algorithms(with optimal step-size) are introduced based respectively on conjugate gradient, preconditioned conjugate gradient,Levenberg-Marquardt and Quasi-Newton optimization schemes. Secondly, a new problem called non-unitary joint zeroblockdiagonalization is introduced. It encompasses the classical joint zero diagonalization problem. It involves thechoice of a well-chosen cost function and the calculation of quantities such as the complex gradient matrix and thecomplex Hessian matrices. We have therefore proposed three new algorithms (and their optimal step-size version) basedrespectively on conjugate gradient, preconditioned conjugate gradient and Levenberg-Marquardt optimization schemes.Finally, we suggest other approaches based on multi-user joint detection techniques in an underdetermined context wherewe have only one sensor receiving simultaneously several signals. First, we have developed an approach by deflationbased on a successive interferences cancelation technique. Then, we have proposed a second method based on the jointmaximum likelihood sequence estimator which is a variant of the VITERBI algorithm.

Parmi les nombreuses recherches en matière de planification et de contrôle des mouvements pour des applications robotiques, l'humanité n'a jamais atteint un point où les robots seraient parfaitement fonctionnels et autonomes dans des environnements dynamiques. Bien qu'il soit controversé de discuter de la nécessité de ces robots, il est très important d'aborder les problèmes qui nous empêchent de réaliser un tel niveau d'autonomie. Ce travail de recherche tente de résoudre ces problèmes qui séparent ces deux modes de fonctionnement avec un accent particulier sur les incertitudes. Les impossibilités pratiques de capacités de détection précises entraînent une variété d'incertitudes dans les scénarios où le robot est mobile ou l'environnement est dynamique. Ce travail se concentre sur le développement de stratégies intelligentes pour améliorer la capacité de gérer les incertitudes de manière robuste dans les robots humanoïdes et industriels. Premièrement, nous nous concentrerons sur un cadre dynamique d'évitement d'obstacles proposé pour les robots industriels équipés de capteurs de peau pour la réactivité. La planification des chemins et le contrôle des mouvements sont généralement formalisés en tant que problèmes distincts de la robotique, bien qu'ils traitent fondamentalement du même problème. Les espaces de configuration à grande dimension, l'environnement changeant et les incertitudes ne permettent pas la planification en temps réel de mouvement exécutable. L'incapacité fondamentale d'unifier ces deux problèmes nous a amené à gérer la trajectoire planifiée en présence de perturbations et d'obstacles imprévus à l'aide de différents mécanismes d'exécution et de déformation de trajectoire. Le cadre proposé utilise «Stack of Tasks», un contrôleur hiérarchique utilisant des informations de proximité, grâce à un planificateur de chemin réactif utilisant un nuage de points pour éviter les obstacles. Les expériences sont effectuées avec les robots PR2 et UR5 pour vérifier la validité du procédé à la fois en simulation et in-situ. Deuxièmement, nous nous concentrons sur une stratégie pour modéliser les incertitudes des paramètres inertiels d'un robot humanoïde dans des scénarios de tâches d'équilibre. Le contrôle basé modèles est devenu de plus en plus populaire dans la communauté des robots à jambes au cours des dix dernières années. L'idée clé est d'exploiter un modèle du système pour calculer les commandes précises du moteur qui entraînent le mouvement désiré. Cela permet d'améliorer la qualité du suivi du mouvement, tout en utilisant des gains de rétroaction plus faibles, ce qui conduit à une conformité plus élevée. Cependant, le principal défaut de cette approche est généralement le manque de robustesse aux erreurs de modélisation. Dans ce manuscrit, nous nous concentrons sur la robustesse du contrôle de la dynamique inverse à des paramètres inertiels erronés. Nous supposons que ces paramètres sont connus, mais seulement avec une certaine précision. Nous proposons ensuite un contrôleur basé optimisation, rapide d'exécution, qui assure l'équilibre du robot malgré ces incertitudes. Nous avons utilisé ce contrôleur en simulation pour effectuer différentes tâches d'atteinte avec le robot humanoïde HRP-2, en présence de diverses erreurs de modélisation. Les comparaisons avec un contrôleur de dynamique inverse classique à travers des centaines de simulations montrent la supériorité du contrôleur proposé pour assurer l'équilibre du robot. / Amidst a lot of research in motion planning and control in concern with robotic applications, the mankind has never reached a point yet, where the robots are perfectly functional and autonomous in dynamic settings. Though it is controversial to discuss about the necessity of such robots, it is very important to address the issues that stop us from achieving such a level of autonomy. Industrial robots have evolved to be very reliable and highly productive with more than 1.5 million operational robots in a variety of industries. These robots work in static settings and they literally do what they are programmed for specific usecases, though the robots are flexible enough to be programmed for a variety of tasks. This research work makes an attempt to address these issues that separate both these settings in a profound way with special focus on uncertainties. Practical impossibilities of precise sensing abilities lead to a variety of uncertainties in scenarios where the robot is mobile or the environment is dynamic. This work focuses on developing smart strategies to improve the ability to handle uncertainties robustly in humanoid and industrial robots. First, we focus on a dynamical obstacle avoidance framework proposed for industrial robots equipped with skin sensors for reactivity. Path planning and motion control are usually formalized as separate problems in robotics. High dimensional configuration spaces, changing environment and uncertainties do not allow to plan real-time motion ahead of time requiring a controller to execute the planned trajectory. The fundamental inability to unify both these problems has led to handle the planned trajectory amidst perturbations and unforeseen obstacles using various trajectory execution and deformation mechanisms. The proposed framework uses ’Stack of Tasks’, a hierarchical controller using proximity information to avoid obstacles. Experiments are performed on a UR5 robot to check the validity of the framework and its potential use for collaborative robot applications. Second, we focus on a strategy to model inertial parameters uncertainties in a balance controller for legged robots. Model-based control has become more and more popular in the legged robots community in the last ten years. The key idea is to exploit a model of the system to compute precise motor commands that result in the desired motion. This allows to improve the quality of the motion tracking, while using lower feedback gains, leading so to higher compliance. However, the main flaw of this approach is typically its lack of robustness to modeling errors. In this paper we focus on the robustness of inverse-dynamics control to errors in the inertial parameters of the robot. We assume these parameters to be known, but only with a certain accuracy. We then propose a computationally-efficient optimization-based controller that ensures the balance of the robot despite these uncertainties. We used the proposed controller in simulation to perform different reaching tasks with the HRP-2 humanoid robot, in the presence of various modeling errors. Comparisons against a standard inverse-dynamics controller through hundreds of simulations show the superiority of the proposed controller in ensuring the robot balance.

For unmanned aircraft systems to gain full access to the National Airspace System (NAS), they must have the capability to detect and avoid other aircraft. This research focuses on the development of a detect-and-avoid (DAA) system for small unmanned aircraft systems. To safely avoid another aircraft, an unmanned aircraft must detect the intruder aircraft with ample time and distance. Two analytical methods for finding the minimum detection range needed are described. The first method, time-based geometric velocity vectors (TGVV), includes the bank-angle dynamics of the ownship while the second, geometric velocity vectors (GVV), assumes an instantaneous bank-angle maneuver. The solution using the first method must be found numerically, while the second has a closed-form analytical solution. These methods are compared to two existing methods. Results show the time-based geometric velocity vectors approach is precise, and the geometric velocity vectors approach is a good approximation under many conditions. The DAA problem requires the use of a robust target detection and tracking algorithm for tracking multiple maneuvering aircraft in the presence of noisy, cluttered, and missed measurements. Additionally these algorithms needs to be able to detect overtaking intruders, which has been resolved by using multiple radar sensors around the aircraft. To achieve these goals the formulation of a nonlinear extension to R-RANSAC has been performed, known as extended recursive-RANSAC (ER-RANSAC). The primary modifications needed for this ER-RANSAC implementation include the use of an EKF, nonlinear inlier functions, and the Gauss-Newton method for model hypothesis and generation. A fully functional DAA system includes target detection and tracking, collision detection, and collision avoidance. In this research we demonstrate the integration of each of the DAA-system subcomponents into fully functional simulation and hardware implementations using a ground-based radar setup. This integration resulted in various modifications of the radar DSP, collision detection, and collision avoidance algorithms, to improve the performance of the fully integrated DAA system. Using these subcomponents we present flight results of a complete ground-based radar DAA system, using actual radar hardware.