NRI: INT: COLLAB: Co-Robotic Systems for GeoSciences Field Research

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Sand and dust storms are a growing worldwide menace, soil instability and erosion threatens agriculture, and fine sediment compromises ecosystem health of rivers and oceans, all impacting large human populations on nearly every continent. The cumulative effects of these disturbed environments also threaten human well-being through damage of habitation and disruption of transportation. An interdisciplinary collaboration of geoscience, cognitive science, and robotics researchers aims to accelerate and deepen the collection of data about the fluid and materials properties associated with such unstable soils by endowing legged robots with the instrumentation and scientific agenda of agile, novice field assistants. These new robots are capable of general field mobility and are being programmed to think like assistant field geologists in order to develop research strategies in rugged natural environments where measurements are lacking. Overcoming the specific locomotion challenges presented by these environments and developing algorithms and software sufficient to interpret and act on human research needs will greatly advance the field of robotics. The resulting new information about wind, water and materials processes will have bearing on the management of infrastructure and agriculture, and also the response of landscapes to environmental changes.The project focus is to use the geosciences field research setting to test a chain of hypotheses reaching from the formal representation of scientific knowledge to the properties of provably correct algorithms for human-machine pursuit of scientific data. The geoscientific goal is to produce the first comprehensive, time varying maps of soil strength with co-located soil moisture composition and size over the course of rainfall events in a natural landscape. The cognitive science goal is to develop a formalized representation of the cognitive processes underlying field data collection and interpretation that is simultaneously suitable to underlie robotic field assistance algorithms while at the same time advancing the study of human perceptual interpolation and reasoning. The robotics goal is to achieve a provably correct architecture for generating from formalized human task specification a chain of safe, stable online automated legged gait transitions on complex broken terrain that subserve the geoscientist data collection objectives. Two different families of legged robots with a variety of perceptual and geoscientific instrumentation suites will be deployed over natural hillsides under investigation by human geoscientists. Field performance of the resulting human-robot teams will be evaluated according to criteria assessing the degree of robotic mobility and autonomy, the quality and reliability of the resulting geoscientific measurements, and the impact of the collection process on the sampled environment. Advances in legged robot mechanics and intelligent control have brought the field to a threshold where the next major challenges for autonomous mobility can only be formulated and engaged with respect to suites of abstract but formal tasks relative to unstructured environments against which the appropriateness and success of autonomously generated, goal-directed motor behaviors can be precisely measured. Robots endowed with even the rudiments of understanding what measurements are needed where and when by scientists, in order to test their hypotheses, would deepen our insight into the structure of human cognition. They would also open the way toward collecting massive amounts of data at presently unachievably fine spatiotemporal scales, potentially transforming the theoretical and empirical foundations of geoscience.