Autonomous GPR Surveys using the Polar Rover Yeti

The National Science Foundation operates stations on the ice sheets of Antarctica and Greenland to investigate Earth's climate history, life in extreme environments, and the evolution of the cosmos. Understandably, logistics costs predominate budgets due to the remote locations and harsh environments involved. Currently, manual ground-penetrating radar (GPR) surveys must preceed vehicle travel across polar ice sheets to detect subsurface crevasses or other voids. This exposes the crew to the risks of undetected hazards. We have developed an autonomous rover, Yeti, specifically to conduct GPR surveys across polar ice sheets. It is a simple four-wheel-drive, battery-powered vehicle that executes autonomous surveys via GPS waypoint following. We describe here three recent Yeti deployments, two in Antarctica and one in Greenland. Our key objective was to demonstrate the operational value of a rover to locate subsurface hazards. Yeti operated reliably at −30 °C, and it has has good oversnow mobility and adequate GPS accuracy for waypoint-following and hazard georeferencing. It has acquired data on hundreds of crevasse encounters to improve our understanding of heavily crevassed traverse routes and to develop automated crevasse-detection algorithms. Importantly, it helped to locate a previously undetected buried building at the South Pole. Yeti can improve safety by decoupling survey personnel from the consequences of undetected hazards. It also enables higher-quality systematic surveys to improve hazard-detection probabilities, increase assessment confidence, and build datasets to understand the evolution of these regions. Yeti has demonstrated that autonomous vehicles have great potential to improve the safety and efficiency of polar logistics. © 2012 Wiley Periodicals, Inc.

[1]  Ayanna M. Howard,et al.  Calibration and Validation of Earth-Observing Sensors Using Deployable Surface-Based Sensor Networks , 2010, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[2]  Gary E. Phetteplace,et al.  Mobility of a lightweight tracked robot over deep snow , 2006 .

[3]  William Whittaker,et al.  Technology and Field Demonstration of Robotic Search for Antarctic Meteorites , 2000, Int. J. Robotics Res..

[4]  James H. Lever,et al.  Revised solar-power budget for Cool Robot polar science campaigns , 2008 .

[5]  James H. Lever,et al.  Mobility and economic feasibility of the Greenland Inland Traverse (GrIT) , 2011 .

[6]  James H. Lever,et al.  Design of lightweight robots for over-snow mobility , 2009 .

[7]  Arvin Agah,et al.  Survivability, Mobility, and Functionality of a Rover for Radars in Polar Regions , 2004 .

[8]  James H. Lever,et al.  High efficiency fuel sleds for polar traverses , 2012 .

[9]  Arvin Agah,et al.  Mobile Robots for Polar Remote Sensing , 2009 .

[10]  Laura E. Ray,et al.  An autonomous robotic platform for ground penetrating radar surveys , 2012, 2012 IEEE International Geoscience and Remote Sensing Symposium.

[11]  Laura E. Ray,et al.  Design and power management of a solar‐powered “Cool Robot” for polar instrument networks , 2007, J. Field Robotics.

[12]  S. Arcone,et al.  Crevasse detection with GPR across the Ross Ice Shelf, Antarctica , 2004, Proceedings of the Tenth International Conference on Grounds Penetrating Radar, 2004. GPR 2004..

[13]  Ayanna M. Howard,et al.  Developing monocular visual pose estimation for arctic environments , 2010, J. Field Robotics.

[14]  Laura E. Ray,et al.  Development of an autonomous robot for ground penetrating radar surveys of polar ice , 2009, 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[15]  Terrence Fong,et al.  Robotic Scouting for Human Exploration , 2009 .

[16]  Ayanna M. Howard,et al.  Development of a Mobile Arctic Sensor Node for Earth-Science Data Collection Applications , 2010 .

[17]  Laura E. Ray,et al.  Mobility characterization for autonomous mobile robots using machine learning , 2011, Auton. Robots.

[18]  J. H. Lever,et al.  Autonomous robotic ground penetrating radar surveys of ice sheets; Using machine learning to identify hidden crevasses , 2012, 2012 IEEE International Conference on Imaging Systems and Techniques Proceedings.

[19]  Arvin Agah,et al.  Robotic approaches to seismic surveying , 2009 .