There are millions of pieces of space debris in orbit around Earth that pose threats to operating spacecraft. Some of these debris can be attributed to satellite failure, or end-of-life protocols. With a continual increase in commercial satellite launches per year, decommissioned spacecraft act as more debris polluting the space environment. Not only can robotic arms assist with active orbital debris removal to be more sustainable, they also support robotic on-orbit servicing (OOS). Additionally, using a robotic manipulator enables different servicing operations to take place, allowing for life extension capabilities for expired spacecraft. These life extension services allow for a broader application for robotic arms, which includes rendezvous proximity operations and docking. Robotic arms can also be used for assembly and manufacturing cases, establishing a more sustained presence and creating permanent structures in space. When considering any robotic rendezvous maneuvers or servicing, assembly, and manufacturing tasks aboard a spacecraft, it is important for the parent satellite to maintain attitude throughout robot motion, as in a zero gravity setting, any forces created by the robot act as equal and opposite forces applied to the parent spacecraft. The research performed in this thesis aims to create a model to describe changes in attitude throughout planned robot motion, as well as introduce methods for compensating for potential disturbances. Additionally, methods for describing the kinematics of a robot manipulator are presented and the forces and torques experienced by each joint are calculated using Newton-Euler inverse dynamics. Based on a calculated trajectory of the end effector, these torques are propagated to the parent spacecraft to determine the change in angular velocity. The results of this analysis are used to determine the required angular velocity to apply to the parent spacecraft in order to maintain attitude. / Master of Science / There are millions of pieces of space debris in orbit that threaten operating spacecraft. Spacecraft that are no longer working, yet continue to orbit, are considered space debris. As commercial satellite launches increase each year, orbital debris becomes more of a problem. Instead of disregarding broken satellites and adding to the orbital debris problem, robotic arms can be used to help fix and extend the lives of these spacecraft through acts of refueling or docking with an expired satellite to assume control, as well as provide assistance with orbital debris removal. In a broader sense, robotic arms can help two satellites dock together as well as assist in proximity operations. Robotic arms can be used to manufacture parts and build space structures, establishing a more permanent human presence in space. Because these robot servicing tasks can be very precise, it is important for the attached spacecraft to maintain position and orientation. During any servicing, assembly, or manufacturing task, the motion of a robotic arm produces forces that propagate to the parent spacecraft. If the spacecraft were on the ground, these forces would absorb into the ground, not affecting the position or orientation of the spacecraft. In zero gravity, any forces created by the robot arm act as equal and opposite forces applied to the parent spacecraft. These forces can cause shifts in the satellites position and orientation which need to be compensated for. Methods for describing the motion of the robotic arm are presented, and a model for how the parent spacecraft reacts to this motion is created. The results from this analysis are used to determine the appropriate counterforce to apply to the parent spacecraft in order to maintain desired orientation.

Visual inspection in autonomous robotics is a task in which autonomous agents are required to gather visual information of objects of interest, in a manner that ensures safety, efficiency and comprehensive coverage. It is, therefore, crucial for identifying key landmarks, detecting cracks or defects, or reconstructing the observed object for detailed analysis. This thesis delves into the  challenges encountered by autonomous agents in executing such tasks and presents frameworks for scenarios ranging from operations by multiple spacecrafts in close proximity to celestial bodies in Deep Space to terrestrial deployments of Unmanned Aerial Vehicles (UAVs) for inspection of large-scale infrastructures. The research thus pursues two main directions: Firstly, a novel formation control strategy is developed to enable autonomous agents to perform proximity operations safely, efficiently, and accurately in order to map the surface of Small Celestial Bodies (SCBs). This investigation encompasses control and coordination strategies, leveraging a realistic astrodynamic model of the orbital environment to navigate safely around SCBs. Along this direction, the contributions focus on enabling a distributed autonomy framework in the form of a cooperative stereo configuration between two spacecraft, allowing acquisition of 3D topological information of the candidate SCB. The framework employs a Leader-Follower approach, treating the maintenance of the desired stereo-formation as a 6 Degree-of-Freedom (DoF) nonlinear model predictive control (NMPC) problem. The second research direction focuses on addressing the problem of enabling robotic inspection for terrestrial applications. With the growing demand for efficient and reliable inspection techniques to improve in-situ situational awareness, the research concentrates on addressing the problem of obtaining detailed visual scan of available structures without any a priori knowledge of either the environment nor the structures. Thus, the key contributions of the presented work reside in the implementation of a unified autonomy, with the unification drawing it's root from the merging of two distinct research perspectives: Inspection and Exploration planning. The contribution establishes a novel solution by introducing a map-independent approach with a synergistic formulation of a reactive profile-adaptive view-planner coupled with a hierarchical exploration strategy and an environment-invariant scene recognition module. By integrating exploration and inspection methodologies, this research seeks to enhance the capabilities of UAVs in navigating and inspecting unknown structures in unfamiliar environments.  Through theoretical developments, extensive simulations and experimental validations, this thesis contributes to the advancement of the state-of-the-art in visual inspection with autonomous robots. Moreover, the findings extend current capabilities of autonomous agents in the field of space exploration as well as in disaster response and complex infrastructure inspection.

Fundamental aspects of biologically-inspired regulatory mechanisms are considered in a robotics context, using artificial neural-network control systems . Regulatory mechanisms are used to control expression of genes, adaptation of form and behavior in organisms. Traditional neural network control architectures assume networks of neurons are fixed and are interconnected by wires. However, these architectures tend to be specified by a designer and are faced with several limitations that reduce scalability and tractability for tasks with larger search spaces. Traditional methods used to overcome these limitations with fixed network topologies are to provide more supervision by a designer. More supervision as shown does not guarantee improvement during training particularly when making incorrect assumptions for little known task domains. Biological organisms often do not require such external intervention (more supervision) and have self-organized through adaptation. Artificial neural tissues (ANT) addresses limitations with current neural-network architectures by modeling both wired interactions between neurons and wireless interactions through use of chemical diffusion fields. An evolutionary (Darwinian) selection process is used to ‘breed’ ANT controllers for a task at hand and the framework facilitates emergence of creative solutions since only a system goal function and a generic set of basis behaviours need be defined. Regulatory mechanisms are formed dynamically within ANT through superpositioning of chemical diffusion fields from multiple sources and are used to select neuronal groups. Regulation drives competition and cooperation among neuronal groups and results in areas of specialization forming within the tissue. These regulatory mechanisms are also shown to increase tractability without requiring more supervision using a new statistical theory developed to predict performance characteristics of fixed network topologies. Simulations also confirm the significance of regulatory mechanisms in solving certain tasks found intractable for fixed network topologies. The framework also shows general improvement in training performance against existing fixed-topology neural network controllers for several robotic and control tasks. ANT controllers evolved in a low-fidelity simulation environment have been demonstrated for a number of tasks on hardware using groups of mobile robots and have given insight into self-organizing system. Evidence of sparse activity and use of decentralized, distributed functionality within ANT controller solutions are found consistent with observations from neurobiology.

Creating systems that can operate autonomously in complex environments is a challenge for contemporary engineering techniques. Automatic design methods offer a promising alternative, but so far they have not been able to produce agents that outperform manual designs. One such method is evolutionary robotics. It has been shown to be a robust and versatile tool for designing robots to perform simple tasks, but more challenging tasks at present remain out of reach of the method. In this thesis I discuss and attack some problems underlying the scalability issues associated with the method. I present a new technique for evolving modular networks. I show that the performance of modularity-biased evolution depends heavily on the morphology of the robot’s body and present a new method for co-evolving morphology and modular control. To be able to reason about the new technique I develop reformulation framework: a general way to describe and reason about metaoptimization approaches. Within this framework I describe a new heuristic for developing metaoptimization approaches that is based on the technique for co-evolving morphology and modularity. I validate the framework by applying it to a practical task of zero-g autonomous assembly of structures with a fleet of small robots. Although this work focuses on the evolutionary robotics, methods and approaches developed within it can be applied to optimization problems in any domain.

Fundamental aspects of biologically-inspired regulatory mechanisms are considered in a robotics context, using artificial neural-network control systems . Regulatory mechanisms are used to control expression of genes, adaptation of form and behavior in organisms. Traditional neural network control architectures assume networks of neurons are fixed and are interconnected by wires. However, these architectures tend to be specified by a designer and are faced with several limitations that reduce scalability and tractability for tasks with larger search spaces. Traditional methods used to overcome these limitations with fixed network topologies are to provide more supervision by a designer. More supervision as shown does not guarantee improvement during training particularly when making incorrect assumptions for little known task domains. Biological organisms often do not require such external intervention (more supervision) and have self-organized through adaptation. Artificial neural tissues (ANT) addresses limitations with current neural-network architectures by modeling both wired interactions between neurons and wireless interactions through use of chemical diffusion fields. An evolutionary (Darwinian) selection process is used to ‘breed’ ANT controllers for a task at hand and the framework facilitates emergence of creative solutions since only a system goal function and a generic set of basis behaviours need be defined. Regulatory mechanisms are formed dynamically within ANT through superpositioning of chemical diffusion fields from multiple sources and are used to select neuronal groups. Regulation drives competition and cooperation among neuronal groups and results in areas of specialization forming within the tissue. These regulatory mechanisms are also shown to increase tractability without requiring more supervision using a new statistical theory developed to predict performance characteristics of fixed network topologies. Simulations also confirm the significance of regulatory mechanisms in solving certain tasks found intractable for fixed network topologies. The framework also shows general improvement in training performance against existing fixed-topology neural network controllers for several robotic and control tasks. ANT controllers evolved in a low-fidelity simulation environment have been demonstrated for a number of tasks on hardware using groups of mobile robots and have given insight into self-organizing system. Evidence of sparse activity and use of decentralized, distributed functionality within ANT controller solutions are found consistent with observations from neurobiology.

Dans cette thèse nous étudions le fait de localiser complètement un objet connu par vision artificielle, en utilisant une caméra monoculaire, ce qui constitue un problème majeur dans des domaines comme la robotique. Une attention particulière est ici portée sur des applications de robotique spatiale, dans le but de concevoir un système de localisation visuelle pour des opérations de rendez-vous spatial autonome. Deux composantes principales du problème sont abordées: celle de la localisation initiale de l'objet ciblé, puis celle du suivi de cet objet image par image, donnant la pose complète entre la caméra et l'objet, connaissant le modèle 3D de l'objet. Pour la détection, l'estimation de pose est basée sur une segmentation de l'objet en mouvement et sur une procédure probabiliste d'appariement et d'alignement basée contours de vues synthétiques de l'objet avec une séquence d'images initiales. Pour la phase de suivi, l'estimation de pose repose sur un algorithme de suivi basé modèle 3D, pour lequel nous proposons trois différents types de primitives visuelles, dans l'idée de décrire l'objet considéré par ses contours, sa silhouette et par un ensemble de points d'intérêts. L'intégrité du système de localisation est elle évaluée en propageant l'incertitude sur les primitives visuelles. Cette incertitude est par ailleurs utilisée au sein d'un filtre de Kalman linéaire sur les paramètres de vitesse. Des tests qualitatifs et quantitatifs ont été réalisés, sur des données synthétiques et réelles, avec notamment des conditions d'image difficiles, montrant ainsi l'efficacité et les avantages des différentes contributions proposées, et leur conformité avec un contexte de rendez vous spatial. / In this thesis, we address the issue of fully localizing a known object through computer vision, using a monocular camera, what is a central problem in robotics. A particular attention is here paid on space robotics applications, with the aims of providing a unified visual localization system for autonomous navigation purposes for space rendezvous and proximity operations. Two main challenges of the problem are tackled: initially detecting the targeted object and then tracking it frame-by-frame, providing the complete pose between the camera and the object, knowing the 3D CAD model of the object. For detection, the pose estimation process is based on the segmentation of the moving object and on an efficient probabilistic edge-based matching and alignment procedure of a set of synthetic views of the object with a sequence of initial images. For the tracking phase, pose estimation is handled through a 3D model-based tracking algorithm, for which we propose three different types of visual features, pertinently representing the object with its edges, its silhouette and with a set of interest points. The reliability of the localization process is evaluated by propagating the uncertainty from the errors of the visual features. This uncertainty besides feeds a linear Kalman filter on the camera velocity parameters. Qualitative and quantitative experiments have been performed on various synthetic and real data, with challenging imaging conditions, showing the efficiency and the benefits of the different contributions, and their compliance with space rendezvous applications.

No description available.

This project discusses the concepton of a web-based simulation. In particular, it will deal with the development of a robotic Mars Pathfinder simulation delivered via the World Wide Web.

In the past few years, the application of Control Barrier Functions (CBF) and High Order Control Barrier Functions (HOCBF) as a suitable framework to ensure safety for autonomous systems has attracted increasing interest. In particular, autonomous space systems are frequently subject to safety-critical constraints due to the high costs involved in manufacturing and launching. In the present work, the application of a sample data MPC controller subject to CBF and HOCBF constraints is explored as a suitable solution for spacecraft formation flight operations. Specifically, a prototype inspection mission of the International Space Station through a multi-agent formation of CubeSats is explored. Each CubeSat is assumed to be injected in a passive relative orbit around the ISS and controlled such that the state of each agent is maintained within a prescribed safe corridor from its reference relative orbit. Moreover, appropriate conditions on the minimum control authority required to guarantee the constraints satisfaction within the MPC scheme formulation are derived and a numerical procedure to assess the recursive feasibility of the designed controller is presented. Moreover, suitable analytical modifications of the classical CBF and HOCBF constraints definitions are introduced such that the presented sample data MPC control scheme is guaranteed to ensure safety for the state of each agent in between sampling intervals. Lastly, the final control strategy is validated numerically by means of computer simulation. / Under de senaste åren har tillämpningen av Kontrollbarriärfunktioner (CBF) och Högre ordningens kontrollbarriärfunktioner (HOCBF) som ett lämpligt ramverk för att säkerställa säkerhet för autonoma system väckt ett ökande intresse. Autonoma rymdsystem är ett område med särskilt fokus på säkerhetsbegränsningar på grund av de höga tillverknings och uppskjutningskostnaderna. I detta arbete undersöks tillämpningen av en MPC-kontroller med CBF och HOCBF bivillkor för applikation inom formationsflygningsoperationer för rymdfarkoster. Detta görs genom att ett prototypinspektionsuppdrag på Internationella Rymdstationen (ISS) genom en multi-agent formation av CubeSats tas fram. Varje CubeSat är ämnad att injiceras i en passiv relativ omloppsbana runt ISS och styras sådant att varje agents tillstånd bevaras inom en föreskriven säker korridor från dess passiva relativa referensomloppsbana. Lämpliga villkor för den minsta styrbarheten som krävs för att garantera att MPC-schemaformuleringens begränsningar är tillfredsställda härleds, och en numerisk procedur för att bedöma den rekursiva genomförbarheten för den designade kontrollern presenteras. Vidare introduceras lämpliga analytiska modifieringar av de klassiska CBF- och HOCBF-begränsningsdefinitionerna så att det presenterade MPC-kontrollschemat med provdata garanterar säkerheten för varje agents tillstånd mellan dess samplingsintervall. Till sist valideras den slutliga kontrollstrategin numeriskt via datorsimuleringar.

Como tópico de fundamental importância na robótica, o planejamento de rotas tem encontrado excelentes resultados nos últimos anos através da utilização de algoritmos baseados no conceito de árvore de exploração rápida, RRT. No entanto, a aplicação desses métodos em sistemas robóticos espaciais revela um cenário ainda a ser explorado. O comportamento não-holonômico e a presença de singularidades dinâmicas são alguns fatores que dificultam a consideração de obstáculos no planejamento de rotas desses sistemas. Além disso, os trabalhos relacionados ao planejamento de movimento para manipuladores espaciais mostram-se concentrados na estratégia ponto-a-ponto, com interesse especial nos aspectos particulares da dinâmica desses sistemas. De modo geral, para manipuladores espaciais, o planejamento de trajetória envolvendo o desvio de obstáculos depende de uma rota previamente computada. Contudo, essa tarefa carece de formulações ou técnicas solidificadas, sobretudo para manipuladores espaciais de base livre flutuante. Com esta motivação, o trabalho proposto nesta dissertação de mestrado cria um planejador de rotas com suporte a desvio de obstáculos para um manipulador espacial planar de base livre flutuante. O modelo dinâmico utilizado é baseado no conceito de manipulador dinamicamente equivalente e incorporado a um algoritmo baseado no conceito de RRT. / As major challenge in the field of robotics, path planning has experienced successful results in recent years by means of the RRT algorithm. However, the application of such algorithms in space manipulators reveals a scenario yet to be explored. The non-holonomic behavior, added to the presence of dynamic singularities are only a few factors that make collision-avoidance path planning of these systems such a hard task. Besides, works in the field of motion planning of space manipulators often concentrate in the strategy pointto- point, with particular interest in the complex dynamics of such systems. As a rule of thumb, collision-avoidance for space manipulators depends on a previous computed path. However, this task still lacks robust formulations, specially in the case of free-floating manipulators. With this motivation, the proposed work creates a collision-avoiding path planning for a free-floating planar manipulator. The dynamic model is based on the Dynamically Equivalent Manipulator and the concept of Rapidly-Exploring Random Trees serves as a frame for the developed algorithm.