Autonomous GPR surveys using the polar rover Yeti

Abstract

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 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.

Kilometer-scale autonomous navigation in subarctic forests: challenges and lessons learned

“…Deep snow significantly affects UGV mobility. As highlighted by Stansbury et al (2004) and Lever et al (2013), vehicle immobilization is a significant hazard when navigating on snow-covered terrain. We have attempted to manually drive the Warthog on a deep snow cover (i.e., 0.7 m), as shown in Figure 18c.…”

“…The aim of this paper is to present the impact of the boreal forest and winter conditions on autonomous navigation technologies with the goal of enabling true long-term robot autonomy. In this section, we show that while various offroad robotic deployments in winter conditions are documented in the literature, they mostly rely on the GNSS signal for localization (Lever et al, 2013). Vision-based localization approaches have enabled autonomous navigation in GNSS-denied environments.…”