The GREENBOT dataset: Multimodal mobile robotic dataset for a typical Mediterranean greenhouse
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Abstract (arXiv)
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 urlhttps://arm.ual.es/arm-group/dataset-greenhouse-2024/.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). First posted on arXiv 1 Feb 2024.
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Citing papers per year: 2025: 1; 2026: 2.
3 papers.
- 2025The Rosario Dataset v2: Multimodal Dataset for Agricultural Roboticscited by 2
- 2026The S3LI Vulcano Dataset: A Dataset for Multi-Modal SLAM in Unstructured Planetary Environmentscited by 1
- 2026Advanced techniques and applications of LiDAR Place Recognition in Agricultural Environments: A Comprehensive Surveycited by 1
- 2026Advanced techniques and applications of LiDAR Place Recognition in Agricultural Environments: A Comprehensive Survey29 Jan 2026
- 2026The S3LI Vulcano Dataset: A Dataset for Multi-Modal SLAM in Unstructured Planetary Environments27 Jan 2026
- 2025The Rosario Dataset v2: Multimodal Dataset for Agricultural Robotics29 Aug 2025