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Ground Robotic Measurement of Aeolian Processes University of Pennsylvania ScholarlyCommons Departmental Papers (ESE) Department of Electrical & Systems Engineering 8-2017 Ground robotic measurement of aeolian processes Feifei Qian University of Pennsylvania, [email protected] Douglas J. Jerolmack Earth and Environmental Science, University of Pennsylvania, [email protected] Nicholas Lancaster Earth and Ecosystem Sciences, Desert Research Institute, [email protected] George Nikolich Atmospheric Sciences, Desert Research Institute, [email protected] Paul B. Reverdy Electrical and Systems Engineering, University of Pennsylvania, [email protected] See next page for additional authors Follow this and additional works at: https://repository.upenn.edu/ese_papers Part of the Electrical and Computer Engineering Commons, and the Systems Engineering Commons Recommended Citation Feifei Qian, Douglas J. Jerolmack, Nicholas Lancaster, George Nikolich, Paul B. Reverdy, Sonia F. Roberts, Thomas F. Shipley, Robert Scott Van pelt, Ted M. Zobeck, and Daniel E. Koditschek, "Ground robotic measurement of aeolian processes", Aeolian Research 27, 1-11. August 2017. http://dx.doi.org/10.1016/ j.aeolia.2017.04.004 This paper is posted at ScholarlyCommons. https://repository.upenn.edu/ese_papers/788 For more information, please contact [email protected]. Ground robotic measurement of aeolian processes 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 difficulto t 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. We then review how the need to traverse challenging aeolian terrains and simultaneously make high-resolution measurements of critical variables requires enhanced robotic capability. 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. For more information: Kod*lab (http://kodlab.seas.upenn.edu/) Keywords Aeolian processes; Field measurements; Legged robot; Instrumentation; Sand transport; Dust emission; Shear stress partitioning; Reactive planning Disciplines Electrical and Computer Engineering | Engineering | Systems Engineering Author(s) Feifei Qian, Douglas J. Jerolmack, Nicholas Lancaster, George Nikolich, Paul B. Reverdy, Sonia F. Roberts, Thomas F. Shipley, Robert Scott Van pelt, Ted M. Zobeck, and Daniel E. Koditschek This journal article is available at ScholarlyCommons: https://repository.upenn.edu/ese_papers/788 Aeolian Research 27 (2017) 1–11 Contents lists available at ScienceDirect Aeolian Research journal homepage: www.elsevier.com/locate/aeolia Review Article Ground robotic measurement of aeolian processes ⇑ Feifei Qian a, , Douglas Jerolmack b, Nicholas Lancaster c, George Nikolich d, Paul Reverdy a, Sonia Roberts a, Thomas Shipley e, R. Scott Van Pelt f, Ted M. Zobeck f,1, Daniel E. Koditschek a a Electrical and Systems Engineering, University of Pennsylvania, USA b Earth and Environmental Science, University of Pennsylvania, USA c Earth and Ecosystem Sciences, Desert Research Institute, USA d Atmospheric Sciences, Desert Research Institute, USA e Psychology, Temple University, USA f Agricultural Research Service, US Department of Agriculture, USA2 article info abstract Article history: Models of aeolian processes rely on accurate measurements of the rates of sediment transport by wind, Received 16 December 2016 and careful evaluation of the environmental controls of these processes. Existing field approaches typi- Revised 22 April 2017 cally require intensive, event-based experiments involving dense arrays of instruments. These devices Accepted 24 April 2017 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 Keywords: in robotics show great promise for assisting and amplifying scientists’ efforts to increase the spatial Aeolian processes and temporal resolution of many environmental measurements governing sediment transport. The emer- Field measurements Legged robot gence of cheap, agile, human-scale robotic platforms endowed with increasingly sophisticated sensor and Instrumentation motor suites opens up the prospect of deploying programmable, reactive sensor payloads across complex Sand transport terrain in the service of aeolian science. Dust emission This paper surveys the need and assesses the opportunities and challenges for amassing novel, highly Shear stress partitioning resolved spatiotemporal datasets for aeolian research using partially-automated ground mobility. We Reactive planning 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 experi- ments. We then review how the need to traverse challenging aeolian terrains and simultaneously make high-resolution measurements of critical variables requires enhanced robotic capability. Finally, we con- clude 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. Ó 2017 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Contents 1. Introduction . ........................................................................................................ 2 2. Field measurements of aeolian processes – current status and challenges . ............................................... 3 2.1. Spatio-temporal resolution of erosivity measurements . ........................................................ 3 2.2. Spatio-temporal resolution of erodibility measurements . ........................................................ 3 3. A ground robotic platform for aeolian research . .................................................................. 4 3.1. Mobile robotic platforms for environmental monitoring . ........................................................ 4 3.2. An example – the RHex robot platform . ........................................................................... 5 ⇑ Corresponding author at: Room 475 Levine, 3330 Walnut St, Philadelphia, PA 19104, USA. E-mail address: [email protected] (F. Qian). 1 Retired from. 2 USDA is an equal opportunity employer and provider. Mention of trade names is for information purposes only and does not imply endorsement by USDA. http://dx.doi.org/10.1016/j.aeolia.2017.04.004 1875-9637/Ó 2017 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). 2 F. Qian et al. / Aeolian Research 27 (2017) 1–11 3.3. Field trials with RHex . .............................................................................. 6 3.3.1. Comparison of data sets from RHex with those taken conventionally ................................................ 6 3.3.2. Potential for new insights from mobility . ................................................................... 7 4. Present and future opportunities for ground robotic measurement of aeolian processes . .................................. 8 4.1. Present opportunities for increasing spatiotemporal resolution of aeolian process measurements . ........................ 8 4.2. Future opportunities for autonomous robotic measurement platforms . ........................................... 9 4.3. Perspectives for future work. ............................................................................. 10 Acknowledgements . .......................................................................................... 10 References . .........................................................................................................
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