用于小行星撞击研究的原位表征的纳米着陆器网络
Network of Nano-Landers for In-Situ Characterization of Asteroid Impact Studies
摘要：
对小行星和彗星的探索可以使人们深入了解太阳系的起源，并有助于行星防御和就地资源利用。小行星，由于其低重力是一个具有挑战性的目标，表面探索。目前的任务设想在小行星表面进行接触和行动。在这项工作中，我们分析了发送数十个纳米着陆器的可行性，每个着陆器的质量为1公斤，体积为1U或1000立方厘米。这些着陆器将跳跃，滚动和飞越小行星表面。着陆器将包括科学仪器，如立体相机，手持镜头成像仪和光谱仪，以表征岩石成分。位于小行星表面的纳米着陆器网络可以提供撞击小行星表面的航天器的独特和非常详细的测量结果。对小行星进行全面的人工撞击实验可有助于确定其组成和地质特征，并有助于开发用于行星防御的小行星偏转技术。几十个纳米着陆器可以提供撞击、由此产生的地震活动和喷出物轨迹的多个互补视图。纳米着陆器可以分析原始的、未出土的风化层，这些风化层不受紫外线和宇宙射线的影响，可能有数百万年的历史。我们制定这一任务概念的方法利用了空间系统规划和设计中的自动化机器学习技术。我们使用达尔文选择的形式来选择和确定合适数量的纳米着陆器，机载仪器和控制系统，以探索和导航小行星环境。在模拟中生成各种设想，并根据可量化的飞行任务目标进行评价，例如在小行星上探测的区域和从撞击事件中记录的数据量。
英文摘要：
Exploration of asteroids and comets can give insight into the origins of the solar system and can be instrumental in planetary defence and in-situ resource utilization (ISRU). Asteroids, due to their low gravity are a challenging target for surface exploration. Current missions envision performing touch-and-go operations over an asteroid surface. In this work, we analyse the feasibility of sending scores of nano-landers, each 1 kg in mass and volume of 1U, or 1000 cm3. These landers would hop, roll and fly over the asteroid surface. The landers would include science instruments such as stereo cameras, hand-lens imagers and spectrometers to characterize rock composition. A network of nano-landers situated on the surface of an asteroid can provide unique and very detailed measurements of a spacecraft impacting onto an asteroid surface. A full-scale, artificial impact experiment onto an asteroid can help characterize its composition and geology and help in the development of asteroid deflection techniques intended for planetary defence. Scores of nano-landers could provide multiple complementary views of the impact, resultant seismic activity and trajectory of the ejecta. The nano-landers can analyse the pristine, unearthed regolith shielded from effects of UV and cosmic rays and that may be millions of years old. Our approach to formulating this mission concepts utilizes automated machine learning techniques in the planning and design of space systems. We use a form of Darwinian selection to select and identify suitable number of nano-landers, the on-board instruments and control system to explore and navigate the asteroid environment. Scenarios are generated in simulation and evaluated against quantifiable mission goals such as area explored on the asteroid and amount of data recorded from the impact event.
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