Egerstedt, Magnus B.

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Now showing 1 - 10 of 308
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    Specification-Based Task Orchestration for Multi-Robot Aerial Teams
    (Georgia Institute of Technology, 2022-08-11) Banks, Christopher J.
    As humans begin working more frequently in environments with multi-agent systems, they are presented with challenges on how to control these systems in an intuitive manner. Current approaches tend to limit either the interaction ability of the user or limit the expressive capacity of instructions given to the robots. Applications that utilize temporal logics provide a human-readable syntax for systems that ensures formal guarantees for specification completion. By providing a modality for global task specification, we seek to reduce cognitive load and allow for high-level objectives to be communicated to a multi-agent system. In addition to this, we also seek to expand the capabilities of swarms to understand desired actions via interpretable commands retrieved from a human. In this thesis, we first present a method for specification-based control of a quadrotor. We utilize quadrotors as a highly agile and maneuverable application platform that has a wide variety of uses in complex problem domains. Leveraging specification-based control allows us to formulate a specification-based planning framework that will be utilized throughout the thesis. We then present methods for creating systems which allows us to provide task decomposition, allocation and planning for a team of quadrotors defined as task orchestration of multi-robot systems. Next, the task allocation portion of the task orchestration work is extended in the online case by considering cost agnostic sampling of trajectories from an online optimization problem. Then, we will introduce learning techniques where temporal logic specifications are learned and generated from a set of user given traces. Finally, we will conclude this thesis by presenting an extension to the Robotarium through hardware and software modifications that provides remote users access to control aerial swarms.
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    Optimization-based Approaches to Safety-Critical Control with Applications to Space Systems
    (Georgia Institute of Technology, 2021-07-30) Mote, Mark Leo
    This thesis investigates the problem of safety-critical control for complex cyber-physical systems, with an emphasis on numerical optimization and autonomy applications in the space domain. First, a set-based approach is introduced for specifying mission constraints, and safety is formalized in the context of a set invariance framework. Next, the research investigates the problem of run time assurance (RTA), which relates to a control system architecture where a performance-oriented controller is augmented with a safety-driven element that filters the control signal in such a way that guarantees safety. The latter part of the thesis consists of application-specific research on various space systems. Autonomous rendezvous proximity operations and docking (ARPOD) is considered under proximity, collision-avoidance, and speed constraints. Natural motion trajectories are used to identify a set of passively safe parking orbits under the Clohessy-Wiltshire-Hill dynamics, and a mixed integer programming approach is used to generate safety-constrained optimal transfer trajectories to this set. The formulation is encoded into an RTA framework. The safety problem is considered for a torque-controlled spacecraft in free rotational motion, subject to line-of-sight constraints. A nondeterministic dynamics model is considered, and an RTA filter is constructed that relies on online computation of forward reachable sets around a recovery maneuver. The approach utilizes recent results from reachability theory in addition to optimization-based computation of invariant sets. Safety guarantees exist when a disturbance torque is bounded. The practicality of the approach is demonstrated with an application on a hardware testbed. Finally, the research studies the topic of harnessing collisional behavior for free-flying spacecraft. A framework is proposed for collision-inclusive trajectory optimization. Experimental comparisons of trajectories with and without collision-avoidance requirements demonstrate the capability of the collision-inclusive strategy to achieve significant performance improvements in realistic scenarios. Additionally, a safety application is considered, and the planner is utilized for the purpose of optimally mitigating damage in the presence of an inevitable collision.
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    Barrier Functions and Model Free Safety With Applications to Fixed Wing Collision Avoidance
    (Georgia Institute of Technology, 2021-07-29) Squires, Eric G.
    Robotics is now being applied to a diversity of real-world applications and in many areas such as industrial, medical, and mobile robotics, safety is a critical consideration for continued adoption. In this thesis we therefore investigate how to develop algorithms that improve the safety of autonomous systems using both a model-based and model-free framework. To begin, we make a variety of assumptions (e.g., that a model is known, there is a single safety constraint, there are no communication limits, and that the state can be sensed everywhere), and show how to guarantee the safety of the system. The contribution of the initial approach is a generalization of an existing method for creating a barrier function, which is a function similar to a Lyapunov function that can be used to make safety guarantees. We then investigate relaxing these initial assumptions. In some cases, new additional assumptions are required, performance may be reduced, or safety guarantees may no longer be available. We motivate the thesis with collision avoidance for fixed wing aircraft which can be viewed as a pairwise constraint on each pair of aircraft. This introduces the need for considering multiple safety factors simultaneously, and we show that an additional assumption is needed in this case. We then relax the assumption that the vehicles have unlimited communication and find that safety can still be guaranteed. However, it is possible in this case that the overriding safety controller may be more invasive than if more communication is allowed. When we then further relax the assumption that the state can be sensed at all times, safety can still be guaranteed in some specified situations but the system may be more permissive in approaching safety boundaries. We finally remove the assumption of a known model for dynamics. Although removing this assumption means the system is no longer guaranteed to be safe, the benefit is that it allows a safety designer to build a far less invasive override to get more performance out of the system.
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    Collective behavior and task persistification in lazy and minimalist collectives
    (Georgia Institute of Technology, 2021-05-10) Dutta, Bahnisikha
    When individuals in a collective system are constrained in terms of sensing, memory, computation, or power reserves; the design of algorithms to control them becomes challenging. These individual limitations can be due to multiple reasons like the shrinking size of each agent for bulk manufacturing efficiency or enforced simplicity to attain cost efficiency. Whereas, in some areas like nano-medicine, the nature of the task itself warrants such simplicity. This thesis presents algorithms inspired by biological and statistical physics models to achieve useful collective behavior through simple local physical interactions and, minimalist approaches to persistify tasks for long durations in collectives with limited capabilities and energy reserves. The first part of the thesis presents a system of vibration-driven robots that embodies the features of simplicity described above. A combination of theory, experiment, and simulation is used to study dynamic aggregation behavior in these robots facilitated via short-range physical attraction potentials between agents. Collectives in a dynamically aggregated state are shown to be capable of transporting objects over relatively long distances in a finite arena. In the rest of the thesis, two different, yet complementary systems are studied and elaborated to highlight the usefulness of distributed inactivity and activity modulation in aiding persistification of tasks in collectives incapable of implementing complicated algorithms to incorporate regular energy replenishing cycles. To summarize, an approach to achieving dynamic aggregation and related tasks like object transport in a constrained brushbot system is described. Two different artificial and biological collective systems are explored to reveal strategies through which tasks can be persistified without requiring complicated computations, sensing, and memory.
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    Long-duration robot autonomy: From control algorithms to robot design
    (Georgia Institute of Technology, 2020-07-27) Notomista, Gennaro
    The transition that robots are experiencing from controlled and often static working environments to unstructured and dynamic settings is unveiling the potential fragility of the design and control techniques employed to build and program them, respectively. A paramount of example of a discipline that, by construction, deals with robots operating under unknown and ever-changing conditions is long-duration robot autonomy. In fact, during long-term deployments, robots will find themselves in environmental scenarios which were not planned and accounted for during the design phase. These operating conditions offer a variety of challenges which are not encountered in any other discipline of robotics. This thesis presents control-theoretic techniques and mechanical design principles to be employed while conceiving, building, and programming robotic systems meant to remain operational over sustained amounts of time. Long-duration autonomy is studied and analyzed from two different, yet complementary, perspectives: control algorithms and robot design. In the context of the former, the persistification of robotic tasks is presented. This consists of an optimization-based control framework which allows robots to remain operational over time horizons that are much longer than the ones which would be allowed by the limited resources of energy with which they can ever be equipped. As regards the mechanical design aspect of long-duration robot autonomy, in the second part of this thesis, the SlothBot, a slow-paced solar-powered wire-traversing robot, is presented. This robot embodies the design principles required by an autonomous robotic system 1in order to remain functional for truly long periods of time, including energy efficiency, design simplicity, and fail-safeness. To conclude, the development of a robotic platform which stands at the intersection of design and control for long-duration autonomy is described. A class of vibration-driven robots, the brushbots, are analyzed both from a mechanical design perspective, and in terms of interaction control capabilities with the environment in which they are deployed.
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    Coverage control: From heterogeneous robot teams to expressive swarms
    (Georgia Institute of Technology, 2020-07-27) Santos Fernandez, Maria Teresa
    Coverage control constitutes a canonical multi-robot coordination strategy that allows a collection of robots to distribute themselves over a domain to optimally monitor the relevant features of the environment. This thesis examines two different aspects of the coverage problem. On the one hand, we investigate how coverage should be performed by a multi-robot team with heterogeneous sensor equipment in the presence of qualitatively different types of events or features in the domain, which may evolve over time. To this end, different information exchange strategies among the robots are considered, and the performance of the resulting distributed control laws is compared experimentally on a team of mobile robots. In addition, we present a constraint-based approach that allows the multi-robot team to cover different types of features whose locations in the domain may evolve other time. On the other hand, in the context of swarm robotics in the arts, this thesis investigates how the coverage paradigm, which affords the control of the entire multi-robot team through the high-level specification of density functions, can serve as an effective interaction modality for artists to effectively utilize robotic swarms in different forms of art expression. In particular, we explore the use of coverage, along with other standard multi-robot control algorithms, to create emotionally expressive behaviors for robot theatre applications. Furthermore, the heterogeneous coverage framework developed in this thesis is employed to interactively control desired concentrations of color throughout a canvas for the purpose of artistic multi-robot painting.
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    Heterogeneous interaction modalities for shape-similar formations
    (Georgia Institute of Technology, 2020-03-18) Buckley, Ian Howell
    Formation control of multi-robot teams is fundamentally influenced by the available sensing and communication capabilities of individual robots. The significance of these capabilities manifests in the network topology induced by interaction modalities present in the team, which may include maintenance of relative distances, bearings, or angles in the formation. To understand this significance and aid in design of effective control strategies, this thesis investigates the interplay between network topology and heterogeneous interaction modalities present in multi-robot formations. With regard to this investigation, each chapter of this thesis addresses a series of research questions that motivate and drive the results. The thesis begins by considering formations in which the relative angles between robots are maintained. To characterize such formations, infinitesimal shape-similarity is developed to describe frameworks in which angle maintenance renders the framework invariant to infinitesimal translations, rotations, and uniform scaling. After developing tools for assessing frameworks for this property, design of formation controllers for infinitesimally shape-similar frameworks reveals the sensing and communication requirements on the robots executing them. To explore relaxations of these requirements, a bearing-only self-assembly mechanism for a class of infinitesimally shape-similar frameworks is designed, and a formation-control strategy is developed to leverage a single distance measurement, suggesting that heterogeneity may be exploited at large. To relate heterogeneous distance, bearing, and angle constraints, the relationships between infinitesimal rigidity, bearing-rigidity, and shape-similarity are examined, espousing the coupling of network topology and interaction modalities in a team. The motions of formations specified by heterogeneous constraints are then characterized, and formation-control strategies are developed. Ultimately, this thesis demonstrates that the coupling of the network topology and heterogeneous interaction modalities of multi-robot teams should be accounted for explicitly to assess the tradeoffs between connectivity and information access in achieving effective formation control.
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    Local encounters in robot swarms: From localization to density regulation
    (Georgia Institute of Technology, 2019-11-11) Mayya, Siddharth
    In naturally occurring swarms---living as well as non-living---local proximity encounters among individuals or particles in the collective facilitate a broad range of emergent phenomena. In the context of robot swarms operating with limited sensing and communication capabilities, this thesis demonstrates how the systematic analysis of inter-robot encounters can enable the swarm to perform useful functions without the presence of a central coordinator. We combine ideas from stochastic geometry, statistical mechanics, and biology to develop mathematical models which characterize the nature and frequency of inter-robot encounters occurring in a robot swarm. These models allow the swarm to perform functions like localization, task allocation, and density regulation, while only requiring individual robots to measure the presence of other robots in the immediate vicinity---either via contact sensors or binary proximity detectors. Moreover, the resulting encounter-based algorithms require no communication among the robots or the presence of a central coordinator, and are robust to individual robot failures occurring in the swarm. Throughout the thesis, experiments conducted on real robot swarms vindicate the idea that inter-robot encounters can be advantageously leveraged by individuals in the swarm.
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    Specification composition and controller synthesis for robotic systems
    (Georgia Institute of Technology, 2019-03-21) Glotfelter, Paul
    From precision agriculture to autonomous-transportation systems, robotic systems have been proposed to accomplish a number of tasks. However, these systems typically require satisfaction of multiple constraints, such as safety or connectivity maintenance, while completing their primary objectives. The objective of this thesis is to endow robotic systems with a Boolean-composition and controller-synthesis framework for specifications of objectives and constraints. Barrier functions represent one method to enforce such constraints via forward set invariance, and Lyapunov functions offer a similar guarantee for set stability. This thesis focuses on building a system of Boolean logic for barrier and Lyapunov functions by using min and max operators. As these objects inherently introduce nonsmoothness, this thesis extends the theory on barrier functions to nonsmooth barrier functions and, subsequently, to controlled systems via control nonsmooth barrier functions. However, synthesizing controllers with respect to a nonsmooth function may create discontinuities; as such, this thesis develops a controller-synthesis framework that, despite creating discontinuities, still produces valid controllers (i.e., ones that satisfy the objectives and constraints). These developments have been successfully applied to a variety of robotic systems, including remotely accessible testbeds, autonomous-transportation scenarios, and leader-follower systems.
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    Power-aware hybrid-dynamical approach to coverage control in multi-robot systems
    (Georgia Institute of Technology, 2018-04-24) Olsen, Mark Ryan
    This thesis develops an algorithm which allows robots in a multi-robot team to optimize for battery power while performing coverage control so as to maximize the mission life of the multi-robot team. We envision a scenario where robots with limited battery supply are executing the well known Lloyd's algorithm in order to effectively cover a certain region. We perform a trade-off between the distance of a robot from the centroid of its Voronoi cell, and the energy required to traverse that distance. In order to execute this trade-off two different strategies are presented -- in one case, the reduction in cost due to coverage is compared against the energy required to traverse the distance to the centroid, and using a user-defined threshold, the decision is made. Then, a more sophisticated algorithm is used to perform the trade-off where the robots solves a switch-time optimization problem to decide whether it should move or it should stay.