Theses and Dissertations from UMD
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New submissions to the thesis/dissertation collections are added automatically as they are received from the Graduate School. Currently, the Graduate School deposits all theses and dissertations from a given semester after the official graduation date. This means that there may be up to a 4 month delay in the appearance of a give thesis/dissertation in DRUM
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Item A FRAMEWORK FOR DEXTEROUS MANIPULATION THROUGH TACTILE PERCEPTION(2022) Ganguly, Kanishka; Aloimonos, Yiannis; Computer Science; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)A long-anticipated, yet hitherto unfilled goal in Robotics research has been to have robotic agents seamlessly integrating with humans in their natural environments, and performing useful tasks alongside humans. While tremendous progress has been made in allowing robots to perceive visually, and understand and reason about the scene, the act of manipulating said environment still remains a challenging and incomplete task.For robotic agents to have capabilities where they can perform useful tasks in environments that are not specifically designed for their operation, it is crucial to have dexterous manipulation capabilities guided by some form of tactile perception. While visual perception provides a large-scale understanding of the environment, tactile perception allows fine-grained understanding of objects and textures. For truly useful robotic agents, a tightly coupled system comprising both visual and tactile perception is a necessity. Tactile sensing hardware can be classified on a spectrum, organized by form-factor on one end to sensing accuracy and robustness on the other. Most off-the-shelf sensors available today trade off one of these features for the other. The tactile sensor used in this research, the BioTac SP, has been selected for its anthropomorphic qualities, such as its shape and sensing mechanism while compromising on quality of sensory outputs. This sensor provides a sensing surface, and returns 24 tactile points of data at each timestamp, along with pressure values. We first present a novel method for contact and motion estimation through visual perception, where we perform non-rigid registration of a human performing actions and compute dense motion estimation trajectories. This is used to compute topological scene changes, and is refined to get object and contact segmentation. We then ground these contact points and motion trajectories to an intermediate action-graph, which can then executed by a robot agent. Secondly, we introduce the concept of computational tactile flow, which is inspired by fMRI studies on humans where it was discovered that the same parts of the brain that react to optical motion stimulus also react to tactile stimulus. We mathematically model the BioTac SP sensor, and interpolate surfaces in two- and three dimensions, on which we compute tactile flow fields. We demonstrate the flow fields on various surfaces, and suggest various useful applications of tactile flow. We next apply tactile feedback to a novel controller, that is able to grasp objects without any prior knowledge about the shape, material, or weight of the objects. We apply tactile flow to compute slippage during grasp, and adjust the finger forces to maintain stable grasp during motion. We demonstrate success on transparent and soft, deformable objects, alongside other regularly shaped samples. Lastly, we take a different approach to processing tactile data, where we compute tactile events taking inspiration from neuromorphic computing literature. We compute spatio-temporal gradients on the raw tactile data, to generate event surfaces, which are more robust and reduces sensor noise. This intermediate surface is then used to track contact regions over the BioTac SP sensor skin, and allows us to detect slippage, track spatial edge contours, and magnitude of applied forces.Item ACTIVE AND PASSIVE MICROFLUIDICS FOR SAMPLE DISCRETIZATION, MANIPULATION AND MULTIPLEXING(2020) Padmanabhan, Supriya; DeVoe, Don L; Chemical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The use of microfluidic technology to compartmentalize an initial sample into discrete and isolated volumes is an important step for many biological and chemical applications, that allows molecules, cells, particles, reagents, and analytes to be spatially constrained, providing unique benefits for their characterization, sorting, and manipulation with low reagent consumption. Discretization can also increase the overall throughput and enable multiplexing. In this dissertation, two platforms are described to enable microfluidic sample discretization and manipulation. First, (2D) microwell arrays fabricated in thermoplastic cyclic olefin copolymer (COP) are explored as a new approach toward the development of high throughput, low-cost components in disposable diagnostics by utilizing a passive discretization technique. Performance of various 2D array designs is characterized numerically and experimentally to assess the impact of thermoplastic surface energy, fluid flow rate, and device geometry on sample filling and discretization. The design principles are used to successfully scale up the platform without affecting device performance. Loop-mediated isothermal amplification (LAMP) on chip is used to demonstrate the platform’s potential for discretized nucleic acid testing. Next, pin spotting in nanoliter-scale 2D arrays is demonstrated as technique for high resolution reagent integration to enable multiplexed testing in diagnostics. The potential for nucleic-acid diagnostics is evaluated by performing rolling circle amplification (RCA) on chip with integrated reagents. Finally, an innovative platform enabling complex discretization and manipulation of aqueous droplets is presented. The system uses simple membrane displacement trap elements as an active technique to perform multiple functions including droplet discretization, release, metering, capture, and merging. Multi-layer polydimethylsiloxane (PDMS) devices with membrane displacement trap (MDT) arrays are used to discretize sample into nanoliter scale droplet volumes, and reliably manipulate individual droplets within the arrays. Performance is characterized for varying capillary number flows, membrane actuation pressures, trap and membrane geometries, and trapped droplet volumes, with operational domains established for each platform function. The novel approach to sample digitization and droplet manipulation is demonstrated through discretization of a dilute bacteria sample, metering of individual traps to generate droplets containing single bacteria, and merging of the resulting droplets to pair the selected bacteria within a single droplet.Item Development and Integration of Tactile Sensing System(2018) Agarwal, Rishabh; Bergbreiter, Sarah; Systems Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)To grasp and manipulate complex objects, robots require information about the interaction between the end effector and the object. This work describes the integration of a low-cost 3-axis tactile sensing system into two different robotic systems and the measurement of some of these complex interactions. The sensor itself is small, lightweight, and compliant so that it can be integrated within a variety of end effectors and locations on those end effectors (e.g. wrapped around a finger). To improve usability and data collection, a custom interface board and ROS (Robot Operating System) package were developed to read the sensor data and interface with the robots and grippers. Sensor data has been collected from four different tasks: 1. pick and place of non-conductive and conductive objects, 2. wrist-based manipulation, 3. peeling tape, and 4. human interaction with a grasped object. In the last task, a closed loop controller is used to adjust the grip force on the grasped object while the human interacts with it.