UMD Theses and Dissertations

Permanent URI for this collectionhttp://hdl.handle.net/1903/3

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 given thesis/dissertation in DRUM.

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Author: search.filters.author.Isbell, Jacob DSubject: search.filters.subject.Echolocation

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    BIO-INSPIRED SONAR IN COMPLEX ENVIRONMENTS: ATTENTIVE TRACKING AND VIEW RECOGNITION
    (2021) Isbell, Jacob D; Horiuchi, Timothy K; Electrical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Bats are known for their unique ability to sense the world through echolocation. This allows them to perceive the world in a way that few animals do, but not without some difficulties. This dissertation explores two such tasks using a bio-inspired sonar system: tracking a target object in cluttered environments, and echo view recognition. The use of echolocation for navigating in dense, cluttered environments can be a challenge due to the need for rapid sampling of nearby objects in the face of delayed echoes from distant objects. If long-delay echoes from a distant object are received after the next pulse is sent out, these “aliased” echoes appear as close-range phantom objects. This dissertation presents three reactive strategies for a high pulse-rate sonar system to combat aliased echoes: (1) changing the interpulse interval to move the aliased echoes away in time from the tracked target, (2) changing positions to create a geometry without aliasing, and (3) a phase-based, transmission beam-shaping strategy to illuminate the target and not the aliasing object. While this task relates to immediate sensing needs and lower level motor loops, view recognition is involved in higher level navigation and planning. Neurons in the mammalian brain (specifically in the hippocampus formation) named “place cells” are thought to reflect this recognition of place and are involved in implementing a spatial map that can be used for path planning and memory recall. We propose hypothetical “echo view cells” that could contribute (along with odometry) to the creation of place cell representations actually observed in bats. We strive to recognize views over extended regions that are many body lengths in size, reducing the number of places to be remembered for a map. We have successfully demonstrated some of this spatial invariance by training feed-forward neural networks (traditional neural networks and spiking neural networks) to recognize 66 distinct places in a laboratory environment over a limited range of translations and rotations. We further show how the echo view cells respond in between known places and how the population of cell outputs can be combined over time for continuity.