Computer Science Theses and Dissertations
Permanent URI for this collectionhttp://hdl.handle.net/1903/2756
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Item Active Vision Based Embodied-AI Design For Nano-UAV Autonomy(2021) Jagannatha Sanket, Nitin; Aloimonos, Yiannis; Computer Science; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The human fascination to mimic ultra-efficient flying beings like birds and bees hasled to a rapid rise in aerial robots in the recent decade. These aerial robots now posses a market share of over 10 Billion US Dollars. The future for aerial robots or Unmanned Aerial Vehicles (UAVs) which are commonly called drones is very bright because of their utility in a myriad of applications. I envision drones delivering packages to our homes, finding survivors in collapsed buildings, pollinating flowers, inspecting bridges, performing surveillance of cities, in sports and even as pets. In particular, quadrotors have become the go to platform for aerial robotics due to simplicity in their mechanical design, their vertical takeoff and landing capabilities and agility characteristics. Our eternal pursuit to improve drone safety and improve power efficiency has givenrise to the research and development of smaller yet smarter drones. Furthermore, smaller drones are more agile and task-distributable as swarms. Embodied Artificial Intelligence (AI) has been a big fuel to push this area further. Classically, the approach to designing such nano-drones possesses a strict distinction between perception, planning and control and relies on a 3D map of the scene that are used to plan paths that are executed by a control algorithm. On the contrary, nature’s never-ending quest to improve the efficiency of flyingagents through genetic evolution led to birds developing amazing eyes and brains tailored for agile flight in complex environments as a software and hardware co-design solution. In contrast, smaller flying agents such as insects that are at the other end of the size and computation spectrum adapted an ingenious approach – to utilize movement to gather more information. Early pioneers of robotics remarked at this observation and coined the concept of “Active Perception” which proposed that one can move in an exploratory way to gather more information to compensate for lack of computation and sensing. Such a controlled movement imposes additional constraints on the data being perceived to make the perception problem simpler. Inspired by this concept, in this thesis, I present a novel approach for algorithmicdesign on nano aerial robots (flying robots the size of a hummingbird) based on active perception by tightly coupling and combining perception, planning and control into sensorimotor loops using only on-board sensing and computation. This is done by re-imagining each aerial robot as a series of hierarchical sensorimotor loops where the higher ones require the inner ones such that resources and computation can be efficiently re-used. Activeness is presented and utilized in four different forms to enable large-scale autonomy at tight Size, Weight, Area and Power (SWAP) constraints not heard of before. The four forms of activeness are: 1. By moving the agent itself, 2. By employing an active sensor, 3. By moving a part of the agent’s body, 4. By hallucinating active movements. Next, to make this work practically applicable I show how hardware and software co-design can be performed to optimize the form of active perception to be used. Finally, I present the world’s first prototype of a RoboBeeHive that shows how to integrate multiple competences centered around active vision in all it’s glory. Following is a list of contributions of this thesis: • The world’s first functional prototype of a RoboBeeHive that can artificially pollinateflowers. • The first method that allows a quadrotor to fly through gaps of unknown shape,location and size using a single monocular camera with only on-board sensing and computation. • The first method to dodge dynamic obstacles of unknown shape, size and locationon a quadrotor using a monocular event camera. Our series of shallow neural networks are trained in simulation and transfers to the real world without any finetuning or re-training. • The first method to detect unmarked drones by detecting propellers. Our neuralnetwork is trained in simulation and transfers to the real world without any finetuning or re-training. • A method to adaptively change the baseline of a stereo camera system for quadrotornavigation. • The first method to introduce the usage of saliency to select features in a directvisual odometry pipeline. • A comprehensive benchmark of software and hardware for embodied AI whichwould serve as a blueprint for researchers and practitioners alike.Item Optimization of Signal Routing in Disruption-Tolerant Networks(2021) Singam, Caitlyn; Ephremides, Anthony; Systems Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Communication networks are prone to disruption due to inherent uncertainties such as environmental conditions, system outages, and other factors. However, current state-of-the-art communication protocols are not yet optimized for communication in highly disruption-prone environments, such as deep space, where the risk of such uncertainties is not negligible. This work involves the development of a novel protocol for disruption-tolerant communication across space-based networks that avoids idealized assumptions and is consistent with system limitations. The proposed solution is grounded in an approach to information as a time-based commodity, and on reframing the problem of efficient signal routing as a problem of value optimization. The efficacy of the novel protocol was evaluated via a custom Monte Carlo simulation against other state-of-the-art protocols in terms of maintaining both data integrity and transmission speed, and was found to provide a consistent advantage across both metrics of interest.Item Synchronized Swimming and Formation Control for Fish-inspired Underwater Vehicles(2019) ghanem, paul; Paley, Derek; Systems Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Multi-vehicle underwater control has different applications in oceanographic sampling and water pollution monitoring. Previous work in this field generated control laws that stabilizes parallel and circular formations of self-propelled particles in addition to consensus control laws in Euclidean space and nonlinear spaces. This thesis presents second order distributed control systems that generate velocity and phase consensus, parallel motion and circular motion for a number of nonlinear agents on the tangent bundle of the $N$-torus. The nonlinear agents considered in this work are underwater fish inspired vehicles modeled by Chaplygin sleigh dynamics. This work uses the Laplacian matrix of a connected interaction graph to achieve phase and velocity consensus on a periodic orbit and to generate average circular motion of all the agents on the same circle. Second, a phase potential is used to generate average parallel motion. Results are illustrated using numerical simulations.Item Central Compact-Reconstruction WENO Methods(2018) Cooley, Kilian; Baeder, James D; Applied Mathematics and Scientific Computation; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)High-order compact upwind schemes produce block-tridiagonal systems due to performing the reconstruction in the characteristic variables, which is necessary to avoid spurious oscillations. Consequently they are less efficient than their non-compact counterparts except on high-frequency features. Upwind schemes lead to many practical drawbacks as well, so it is desirable to have a compact scheme that is more computationally efficient at all wavenumbers that does not require a characteristic decomposition. This goal cannot be achieved by upwind schemes so we turn to the central schemes, which by design require neither a Riemann solver nor a determination of upwind directions by characteristic decomposition. In practice, however, central schemes of fifth or higher order apparently need the characteristic decomposition to fully avoid spurious oscillations. The literature provides no explanation for this fact that is entirely convincing; however, a comparison of two central WENO schemes suggests one. Pursuing that possibility leads to the first main contribution of this work, which is the development of a fifth-order, central compact-reconstruction WENO (CCRWENO) method. That method retains the key advantages of central and compact schemes but does not entirely avoid characteristic variables as was desired. The second major contribution is to establish that the role of characteristic variables is to to make flux Jacobians within a stencil more diagonally dominant, having ruled out some plausible alternative explanations. The CCRWENO method cannot inherently improve the diagonal dominance without compromising its key advantages, so some strategies are explored for modifying the CCRWENO solution to prevent the spurious oscillations. Directions for future investigation and improvement are proposed.Item GRAPH-BASED METHODS FOR PATH PLANNING WITH DYNAMIC OBSTACLES USING LINEAR TEMPORAL LOGIC(2018) Han, Wenqi; Herrmann, Jeffrey; Systems Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Autonomous vehicles are expected to play a key role in rescue and transportation. Planning an optimal path with the minimum computational effort for these vehicles in their missions improves their efficiency and adds safety for the vehicles and third parties on the ground. The objective of this thesis is to study the computational effort of four planning methods that implement linear temporal logic (LTL) to translate the high-level mission requirements and environmental specifications. The Potential Field Method and the Critical Path method required less computational effort to find one of the shortest paths for the mission The Multigraph Network Planning method and the Critical Path method can find all the possible paths with predetermined path length. The Random Walk method required more computational effort and memory compared to the other three methods.Item Distributed Search Method for Teams of Small Unmanned Aircraft Systems(2018) Moschler, Jacob D.; Baras, John S; Systems Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)We apply Model Based Systems Engineering (MBSE) methods to develop requirements for unmanned aircraft systems (UAS) use cases across industries and create new path planning algorithms for one group of use cases with similar requirements. We then develop and validate models to estimate cost versus data quality for the aforementioned group of use cases. We use our models in conjunction with the MBSE process to plan and execute flights beyond visual line of sight (BVLOS) to scan large areas of remote jungle using small UAS.Item A Graph Transformation Method for Robotic Satellite Servicing Down-Selection(2017) Knizhnik, Jessica; Austin, Mark; Systems Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)As remote robotic space satellite servicing technologies develop, each servicer satellite will need to account for a number of servicing scenarios and consider a variety of alternate design solutions to best meet the most servicing scenario requirements. This thesis presents a graph transformation method for systematically down-selecting the number of design options available, and highlighting trade-offs in sets of design solutions which best meet satellite servicing task requirements while also reducing total mass, maximum power needed and servicing time. The proposed method successfully identifies for further consideration several best design solutions from a set of approximately 10,000 potential solutions in the first test case examined, and from a set of approximately 2*1026 in the second test case examined.Item Mission and Scenario Planning for Unmanned Aerial Vehicles (Path Planning and Collision Avoidance Systems)(2016) Shadab, Niloofar; Xu, Huan; Systems Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)As unmanned autonomous vehicles (UAVs) are being widely utilized in military and civil applications, concerns are growing about mission safety and how to integrate dierent phases of mission design. One important barrier to a coste ective and timely safety certication process for UAVs is the lack of a systematic approach for bridging the gap between understanding high-level commander/pilot intent and implementation of intent through low-level UAV behaviors. In this thesis we demonstrate an entire systems design process for a representative UAV mission, beginning from an operational concept and requirements and ending with a simulation framework for segments of the mission design, such as path planning and decision making in collision avoidance. In this thesis, we divided this complex system into sub-systems; path planning, collision detection and collision avoidance. We then developed software modules for each sub-systemItem Compact-Reconstruction Weighted Essentially Non-Oscillatory Schemes for Hyperbolic Conservation Laws(2013) Ghosh, Debojyoti; Baeder, James D; Applied Mathematics and Scientific Computation; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)A new class of non-linear compact interpolation schemes is introduced in this dissertation that have a high spectral resolution and are non-oscillatory across discontinuities. The Compact-Reconstruction Weighted Essentially Non-Oscillatory (CRWENO) schemes use a solution-dependent combination of lower-order compact schemes to yield a high-order accurate, non-oscillatory scheme. Fifth-order accurate CRWENO schemes are constructed and their numerical properties are analyzed. These schemes have lower absolute errors and higher spectral resolution than the WENO scheme of the same order. The schemes are applied to scalar conservation laws and the Euler equations of fluid dynamics. The order of convergence and the higher accuracy of the CRWENO schemes are verified for smooth solutions. Significant improvements are observed in the resolution of discontinuities and extrema as well as the preservation of flow features over large convection distances. The computational cost of the CRWENO schemes is assessed and the reduced error in the solution outweighs the additional expense of the implicit scheme, thus resulting in higher numerical efficiency. This conclusion extends to the reconstruction of conserved and primitive variables for the Euler equations, but not to the characteristic-based reconstruction. Further improvements are observed in the accuracy and resolution of the schemes with alternative formulations for the non-linear weights. The CRWENO schemes are integrated into a structured, finite-volume Navier-Stokes solver and applied to problems of practical relevance. Steady and unsteady flows around airfoils are solved to validate the scheme for curvi-linear grids, as well as overset grids with relative motion. The steady flow around a three-dimensional wing and the unsteady flow around a full-scale rotor are solved. It is observed that though lower-order schemes suffice for the accurate prediction of aerodynamic forces, the CRWENO scheme yields improved resolution of near-blade and wake flow features, including boundary and shear layers, and shed vortices. The high spectral resolution, coupled with the non-oscillatory behavior, indicate their suitability for the direct numerical simulation of compressible turbulent flows. Canonical flow problems -- the decay of isotropic turbulence and the shock-turbulence interaction -- are solved. The CRWENO schemes show an improved resolution of the higher wavenumbers and the small-length-scale flow features that are characteristic of turbulent flows. Overall, the CRWENO schemes show significant improvements in resolving and preserving flow features over a large range of length scales due to the higher spectral resolution and lower dissipation and dispersion errors, compared to the WENO schemes. Thus, these schemes are a viable alternative for the numerical simulation of compressible, turbulent flows.