GREENBOT数据集：典型地中海温室的多模态移动机器人数据集
The GREENBOT dataset: Multimodal mobile robotic dataset for a typical Mediterranean greenhouse
AI总结：
本文提出GREENBOT数据集，采集自典型地中海温室，用于测试SLAM方法，支持植物三维建模与机器人喷洒，并验证了其适用性。
摘要：
本文介绍了一个专为具有挑战性的农业环境（温室）而设计的新颖数据集，在该环境中，实现精确定位至关重要。该数据集通过一个配备有移动机器人中常用传感器组的移动平台采集，平台被移动穿过一个种植番茄的典型地中海温室的所有走廊。该数据集为在这种类室内空间中构建植物的详细三维模型提供了独特机会，潜在应用包括机器人化喷洒。据作者所知，这是首次在温室环境中提出一个适用于测试同时定位与建图（SLAM）方法的数据集，该环境带来了独特的挑战。通过展示使用最先进算法得到的SLAM结果，评估了该数据集对此目标的适用性。该数据集在线提供，网址为\url{https://arm.ual.es/arm-group/dataset-greenhouse-2024/}。
英文摘要：
This paper introduces an innovative dataset specifically crafted for challenging agricultural settings (a greenhouse), where achieving precise localization is of paramount importance. The dataset was gathered using a mobile platform equipped with a set of sensors typically used in mobile robots, as it was moved through all the corridors of a typical Mediterranean greenhouse featuring tomato crop. This dataset presents a unique opportunity for constructing detailed 3D models of plants in such indoor-like space, with potential applications such as robotized spraying. For the first time to the best knowledge of authors, a dataset suitable to put at test Simultaneous Localization and Mapping (SLAM) methods is presented in a greenhouse environment, which poses unique challenges. The suitability of the dataset for such goal is assessed by presenting SLAM results with state-of-the-art algorithms. The dataset is available online in \url{https://arm.ual.es/arm-group/dataset-greenhouse-2024/}.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
