Nature Mobility: Autonomous Archives and Environmental Memory

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This dissertation investigates how autonomous robotics, generative systems, and environmental data visualization can function as mobile archives of ecological memory through public encounter and autonomous movement. Responding to climate change, environmental instability, and the increasing separation between urban life and natural ecosystems, the project explores alternative forms of preservation beyond static archives and conventional exhibition spaces.The dissertation centers on Nature Mobility, an artistic robotics project in which an autonomous robot navigates public urban environments while carrying sculptural elements and generative videos created from ecological datasets collected in 2025. These data include salmon population data, weather data such as humidity, air pressure, temperature, wind speed, precipitation, cloud cover, sunrise and sunset times, forest health indices, bird migration intensity, wildfire activity, and whale population records. Using ROS2 based navigation, SLAM, sensor fusion, and TouchDesigner, environmental data is translated into abstract visual systems intended as speculative encodings of ecological conditions rather than literal representations of nature. The robot also engages in AI generated communication with both human and nonhuman entities, producing fragmented and occasionally awkward interactions that challenge conventional expectations of social robotics and technological efficiency. This project has been performed as a public robotic intervention at several Seattle locations, including the Seattle Center, Olympic Sculpture Park, the University of Washington and Green Lake Park. Evaluation is conducted through qualitative observation of audience interaction, interpretive response, and behavioral unpredictability during live encounters. Through this approach, the dissertation examines how autonomous systems, environmental data can function within public space as mobile archives carrying ecological memory across uncertain environmental futures.

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Thesis (Ph.D.)--University of Washington, 2026

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