|QIAN, FEI FEI - University Of Pennsylvania|
|JEROLMACK, DOUGLAS - University Of Pennsylvania|
|LANCASTER, NICHOLAS - Desert Research Institute|
|NICKOLICH, GEORGE - Desert Research Institute|
|REVERDY, PAUL - University Of Pennsylvania|
|ROBERTS, SONIA - University Of Pennsylvania|
|SHIPLEY, THOMAS - Temple University|
|Van Pelt, Robert - Scott|
|ZOEBECK, TED - Retired ARS Employee|
|KODITSCHEK, DANIEL - University Of Pennsylvania|
Submitted to: Aeolian Research
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 4/24/2017
Publication Date: 8/15/2017
Citation: Qian, F., Jerolmack, D., Lancaster, N., Nickolich, G., Reverdy, P., Roberts, S., Shipley, T., Van Pelt, R.S., Zoebeck, T.M., Koditschek, D.E. 2017. Ground robotic measurement of aeolian processes. Aeolian Research. 27:1-11.
Interpretive Summary: Advances in robotics offers the opportunity to acquire data in locations that are inaccessible or dangerous for human operators. However this technology has not been applied to the study of wind erosion. Scientists from ARS (Lubbock, Texas), University of Pennsylvania, Desert Research Institute and Temple University installed instrumentation onto a legged robot and took series of spatially and temporally intensive measurements to prove the concept of robotic movement of expensive instruments to characterize wind flow fields around porous and solid objects and sand transport along the ridgeline of an active sand dune. We found the robot to be an agile and robust method for deploying instrumentation where human involvement would either be hazardous or would influence the data collected. This opens possibilities of having dedicated robots at multiple locations that could instantly respond to wind erosion events at their location, thus removing or reducing the limitations of human research team logistics.
Technical Abstract: Models of aeolian processes rely on accurate measurements of the rates of sediment transport by wind, and careful evaluation of the environmental controls of these processes. Existing field approaches typically require intensive, event-based experiments involving dense arrays of instruments. These devices are often cumbersome and logistically difficult to set up and maintain, especially near steep or vegetated dune surfaces. Significant advances in instrumentation are needed to provide the datasets that are required to validate and improve mechanistic models of aeolian sediment transport. Recent advances in robotics show great promise for assisting and amplifying scientists’ efforts to increase the spatial and temporal resolution of many environmental measurements governing sediment transport. The emergence of cheap, agile, human-scale robotic platforms endowed with increasingly sophisticated sensor and motor suites opens up the prospect of deploying programmable, reactive sensor payloads across complex terrain in the service of aeolian science. This paper surveys the need, and assesses the opportunities and challenges for amassing novel, highly resolved spatiotemporal datasets for aeolian research using partially-automated ground mobility. We review the limitations of existing measurement approaches for aeolian processes, and discuss how they may be transformed by ground-based robotic platforms, using examples from our initial field experiments. Finally, we conclude with a look to the future, in which robotic platforms may operate with increasing autonomy in harsh conditions. Besides expanding the completeness of terrestrial datasets, bringing ground-based robots to the aeolian research community may lead to unexpected discoveries that generate new hypotheses to expand the science itself.