This paper describes a novel approach to simultaneous localization and mapping (SLAM) techniques applied to the autonomous planetary rover exploration scenario to reduce both the relative and absolute localization errors, using two well‐proven techniques: particle filters and scan matching. Continuous relative localization is improved by matching high‐resolution sensor scans to the online created local map. Additionally, to avoid issues with drifting localization, absolute localization is globally corrected at discrete times, according to predefined event criteria, by matching the current local map to the orbiter's global map. The resolutions of local and global maps can be appropriately chosen for computation and accuracy purposes. Further, the online generated local map, of the form of a structured elevation grid map, can also be used to evaluate the traversability of the surrounding environment and allow for continuous navigation. The objective of this study is to support long‐range low‐supervision planetary exploration. The implemented SLAM technique has been validated with a data set acquired during a field test campaign performed at the Teide Volcano on the island of Tenerife, representative of a Mars/Moon exploration scenario.

中文翻译：

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SLAM适用于全球定位的自主行星漫游车

本文介绍了一种新颖的同步定位和制图（SLAM）技术，该技术已应用到自主行星漫游车探索场景中，可通过两种公认的技术来减少相对定位误差和绝对定位误差：粒子滤波和扫描匹配。通过将高分辨率的传感器扫描与在线创建的本地地图相匹配，可以改善连续的相对定位。另外，为了避免出现漂移定位问题，通过将当前本地地图与轨道飞行器的全局地图进行匹配，可以根据预定义的事件准则在离散时间全局校正绝对定位。可以适当地选择局部和全局地图的分辨率，以用于计算和准确性目的。此外，在线生成的本地地图（以结构化的高程网格地图的形式）也可用于评估周围环境的可穿越性，并允许连续导航。这项研究的目的是支持远程低监督行星探索。实施的SLAM技术已通过在特内里费岛的泰德火山上进行的现场测试活动中获得的数据集进行了验证，这是火星/月球勘探场景的代表。