ABSTRACT. VALKYRIE (Very-deep Autonomous Laser-powered Kilowatt-class Yo-yoing Robotic Ice Explorer) is a NASA-funded project to develop key technologies for an autonomous ice penetrator, or cryobot, capable of delivering science payloads through outer planet ice caps and terrestrial glaciers. This 4 year effort will produce a cylindrical cryobot prototype 280 cm in length and 25 cm in diameter. One novel element of VALKYRIE's design is the use of a high-energy laser as the primary power source. 1070 nm laser light is transmitted at 5 kW from a surface-based laser and injected into a customdesigned optical waveguide that is spooled out from the descending cryobot. Light exits the downstream end of the fiber, travels through diverging optics, and strikes an anodized aluminum beam dump, which channels thermal power to hot-water jets that melt the descent hole. Some beam energy is converted to electricity via photovoltaic cells, for running on-board electronics and jet pumps. Since the vehicle can be sterilized prior to deployment, and forward contamination is minimized as the melt path refreezes behind the cryobot, expansions on VALKYRIE concepts may enable cleaner access to deep subglacial lakes. This paper focuses on laser delivery and beam dump thermal design.
The development of algorithms for agile science and autonomous exploration has been pursued in contexts ranging from spacecraft to planetary rovers to unmanned aerial vehicles to autonomous underwater vehicles. In situations where time, mission resources and communications are limited and the future state of the operating environment is unknown, the capability of a vehicle to dynamically respond to changing circumstances without human guidance can substantially improve science return. Such capabilities are difficult to achieve in practice, however, because they require intelligent reasoning to utilize limited resources in an inherently uncertain environment. Here we discuss the development, characterization and field performance of two algorithms for autonomously collecting water samples on VALKYRIE (Very deep Autonomous Laser-powered Kilowatt-class Yo-yoing Robotic Ice Explorer), a glacier-penetrating cryobot deployed to the Matanuska Glacier, Alaska (Mission Control location: 61°42′09.3″N 147°37′23.2″W). We show performance on par with human performance across a wide range of mission morphologies using simulated mission data, and demonstrate the effectiveness of the algorithms at autonomously collecting samples with high relative cell concentration during field operation. The development of such algorithms will help enable autonomous science operations in environments where constant real-time human supervision is impractical, such as penetration of ice sheets on Earth and high-priority planetary science targets like Europa.
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