土卫二
任务(项目管理)
天体生物学
机器人
计算机科学
地形
运动规划
人工智能
搜救
太空探索
航空航天工程
环境科学
遥感
地球科学
地质学
工程类
生态学
物理
生物
系统工程
作者
Tiago Vaquero,Guglielmo Daddi,Rohan Thakker,Michael Paton,Ashkan Jasour,Marlin P. Strub,R. Michael Swan,Rob Royce,Matthew Gildner,Phillipe Tosi,Marcel Veismann,P. Gavrilov,Eloïse Marteau,Joseph Bowkett,Daniel Loret de Mola Lemus,Yashwanth Kumar Nakka,Benjamin Hockman,Andrew L. Orekhov,Tristan Hasseler,Carl Leake
出处
期刊:Science robotics
[American Association for the Advancement of Science]
日期:2024-03-13
卷期号:9 (88)
被引量:14
标识
DOI:10.1126/scirobotics.adh8332
摘要
Ice worlds are at the forefront of astrobiological interest because of the evidence of subsurface oceans. Enceladus in particular is unique among the icy moons because there are known vent systems that are likely connected to a subsurface ocean, through which the ocean water is ejected to space. An existing study has shown that sending small robots into the vents and directly sampling the ocean water is likely possible. To enable such a mission, NASA’s Jet Propulsion Laboratory is developing a snake-like robot called Exobiology Extant Life Surveyor (EELS) that can navigate Enceladus’ extreme surface and descend an erupting vent to capture unaltered liquid samples and potentially reach the ocean. However, navigating to and through Enceladus’ environment is challenging: Because of the limitations of existing orbital reconnaissance, there is substantial uncertainty with respect to its geometry and the physical properties of the surface/vents; communication is limited, which requires highly autonomous robots to execute the mission with limited human supervision. Here, we provide an overview of the EELS project and its development effort to create a risk-aware autonomous robot to navigate these extreme ice terrains/environments. We describe the robot’s architecture and the technical challenges to navigate and sense the icy environment safely and effectively. We focus on the challenges related to surface mobility, task and motion planning under uncertainty, and risk quantification. We provide initial results on mobility and risk-aware task and motion planning from field tests and simulated scenarios.
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