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Data-driven surface traversability analysis for Mars 2020 landing site selection

机译:数据驱动的2020年火星着陆点选择的表面可穿越性分析

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The objective of this paper is three-fold: 1) to describe the engineering challenges in the surface mobility of the Mars 2020 Rover mission that are considered in the landing site selection processs, 2) to introduce new automated traversability analysis capabilities, and 3) to present the preliminary analysis results for top candidate landing sites. The analysis capabilities presented in this paper include automated terrain classification, automated rock detection, digital elevation model (DEM) generation, and multi-ROI (region of interest) route planning. These analysis capabilities enable to fully utilize the vast volume of high-resolution orbiter imagery, quantitatively evaluate surface mobility requirements for each candidate site, and reject subjectivity in the comparison between sites in terms of engineering considerations. The analysis results supported the discussion in the Second Landing Site Workshop held in August 2015, which resulted in selecting eight candidate sites that will be considered in the third workshop.
机译:本文的目标包括三个方面:1)描述着陆地点选择过程中考虑的火星2020 Rover任务在表面机动性方面的工程挑战; 2)介绍新的自动穿越能力分析功能; 3)展示最热门的候选着陆点的初步分析结果。本文介绍的分析功能包括自动地形分类,自动岩石检测,数字高程模型(DEM)生成和多ROI(感兴趣区域)路线规划。这些分析功能可以充分利用大量高分辨率的轨道卫星图像,定量评估每个候选站点的表面迁移率要求,并从工程角度考虑在比较站点之间的主观性。分析结果支持了2015年8月举行的第二次着陆场讲习班的讨论,从而选择了八个候选场址,将在第三次讲习班中进行审议。

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