BASEPROD: The Bardenas Semi-Desert Planetary Rover Dataset.

IF 5.8 2区综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES

Scientific Data Pub Date : 2024-09-27 DOI:10.1038/s41597-024-03881-1

Levin Gerdes, Tim Wiese, Raúl Castilla Arquillo, Laura Bielenberg, Martin Azkarate, Hugo Leblond, Felix Wilting, Joaquín Ortega Cortés, Alberto Bernal, Santiago Palanco, Carlos Pérez Del Pulgar

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Abstract

Dataset acquisitions devised specifically for robotic planetary exploration are key for the advancement, evaluation, and validation of novel perception, localization, and navigation methods in representative environments. Originating in the Bardenas semi-desert in July 2023, the data presented in this Data Descriptor is primarily aimed at Martian exploration and contains relevant rover sensor data from approximately 1.7km of traverses, a high-resolution 3D map of the test area, laser-induced breakdown spectroscopy recordings of rock samples along the rover path, as well as local weather data. In addition to optical cameras and inertial sensors, the rover features a thermal camera and six force-torque sensors. This setup enables, for example, the study of future localization, mapping, and navigation techniques in unstructured terrains for improved Guidance, Navigation, and Control (GNC). The main features of this dataset are the combination of scientific and engineering instrument data, as well as the inclusion of the thermal camera and force-torque sensors in particular.

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BASEPROD：巴登纳斯半沙漠行星漫游车数据集。

专为机器人行星探索设计的数据集采集是在代表性环境中推进、评估和验证新型感知、定位和导航方法的关键。本数据描述程序所提供的数据于 2023 年 7 月在巴登纳斯半沙漠采集，主要用于火星探索，其中包含来自约 1.7 千米穿越路径的相关漫游车传感器数据、测试区域的高分辨率三维地图、漫游车沿途岩石样本的激光诱导击穿光谱记录以及当地天气数据。除了光学相机和惯性传感器外，漫游车还配备了一台热像仪和六个力矩传感器。例如，这种设置可用于研究未来在非结构化地形中的定位、绘图和导航技术，以改进制导、导航和控制（GNC）。该数据集的主要特点是结合了科学和工程仪器数据，特别是包含了热像仪和力扭矩传感器。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Scientific Data Social Sciences-Education

CiteScore

11.20

自引率

4.10%

发文量

689

审稿时长

16 weeks

期刊介绍： Scientific Data is an open-access journal focused on data, publishing descriptions of research datasets and articles on data sharing across natural sciences, medicine, engineering, and social sciences. Its goal is to enhance the sharing and reuse of scientific data, encourage broader data sharing, and acknowledge those who share their data. The journal primarily publishes Data Descriptors, which offer detailed descriptions of research datasets, including data collection methods and technical analyses validating data quality. These descriptors aim to facilitate data reuse rather than testing hypotheses or presenting new interpretations, methods, or in-depth analyses.