Datasets:
License:
| license: other | |
| task_categories: | |
| - object-detection | |
| - image-segmentation | |
| - robotics | |
| - slam | |
| - navigation | |
| language: | |
| - en | |
| - es | |
| tags: | |
| - agriculture | |
| - robotics | |
| - orchards | |
| - alto-valle | |
| - stereo-vision | |
| - lidar | |
| - gnss-rtk | |
| pretty_name: Alto Valle Dataset | |
| size_categories: | |
| - 100G<n<1T | |
| viewer: false | |
| # Alto Valle Dataset | |
| <div align="center"> | |
| <img src="https://raw.githubusercontent.com/Seba-san/AltoValleDataset/main/gifs/abril.gif" width="400"/> | |
| <p><em>Autonomous navigation data in Alto Valle Pear Orchards</em></p> | |
| </div> | |
| ## 📖 Overview | |
| The **Alto Valle Dataset** is a collection of experimental data acquired in pear orchards (*Pyrus communis*) at the **INTA Alto Valle Experimental Station** (Río Negro, Argentina). | |
| The main goal of this dataset is to support the development of **localization, mapping (SLAM), and navigation algorithms** in agricultural environments. It presents unique challenges such as: | |
| * High variability in lighting and terrain. | |
| * Seasonal changes: Data captures during **Summer/Autumn** (leafy, pre-harvest) and **Winter** (leafless, pruning). | |
| * Repetitive structures (rows of trees). | |
| ## 🚜 Hardware & Setup | |
| The data was captured using a modified **N. Blosi Senior** harvesting platform moving at approximately $0.3 m/s$. | |
| | Sensor Type | Model | Specifications | | |
| | :--- | :--- | :--- | | |
| | **Stereo Camera** | **Stereolabs ZED** | 720x1280 @ 15 FPS. USB 3.0 connected to Nvidia Jetson TX1. | | |
| | **LiDAR** | **SICK LMS-100** | 2D LiDAR, 50Hz (stored at 1Hz), 270° FOV, 0.5° resolution. | | |
| | **GNSS-RTK** | **U-BLOX C94-M8P-2** | Base + Rover setup (915MHz link). ~2.5cm accuracy. 1Hz update rate. | | |
| The sensors were mounted 2.5m high, with the camera acting as the reference frame. | |
| ## 📁 Dataset Structure | |
| The dataset is organized by sequences (April and August). Each sequence contains: | |
| ```text | |
| dataset/ | |
| ├── sequenceXX/ | |
| │ ├── images/ | |
| │ │ ├── left_<index>.png # Rectified left image | |
| │ │ ├── right_<index>.png # Rectified right image | |
| │ │ └── timestamps.txt # Image timestamps | |
| │ ├── lidar.csv # LiDAR readings | |
| │ └── gnss.csv # GNSS-RTK readings | |
| ``` | |
| ### Data Format Details | |
| * **Images:** PNG format, rectified. | |
| * **GNSS (`gnss.csv`):** | |
| Format: `[latitude | longitude | timestamp]` | |
| * **LiDAR (`lidar.csv`):** | |
| Format: `[timestamp | nscan | 541 x range]` | |
| * `nscan`: Frame number generated by the sensor. | |
| * `range`: 541 distance values (0.5° angular resolution). | |
| ## 📐 Calibration Parameters | |
| Intrinsic parameters for the **ZED Camera** used in this dataset. The baseline is **120.647 mm**. | |
| | Parameter | Left Camera | Right Camera | | |
| | :--- | :--- | :--- | | |
| | **fx** | 692.964 | 698.848 | | |
| | **fy** | 692.964 | 698.848 | | |
| | **cx** | 576.186 | 737.995 | | |
| | **cy** | 367.798 | 361.795 | | |
| | **k1** | -0.182798 | -0.1634 | | |
| | **k2** | 0.0277213 | 0.0214219 | | |
| *Extrinsic parameters (transformations between sensors) are available in the PDF documentation or the paper.* | |
| ## 📅 Seasons & Conditions | |
| The dataset covers different phenological stages of the pear crops (Williams, Abate Fetel, and Beurré D’Anjou varieties): | |
| 1. **April 09, 2018 (Autumn):** | |
| * **Condition:** Pre-harvest. Dense foliage, branches weighed down by fruit. | |
| * **Weather:** Sunny, variable lighting (shadows/direct sun). | |
| * **Ground:** Presence of weeds, irrigation ditches. | |
| 2. **August 06, 2018 (Winter):** | |
| * **Condition:** Pruning season. Deciduous trees (no leaves). Visible trunks and structure. | |
| * **Weather:** Partly cloudy/overcast. | |
| * **Ground:** Cleared weeds. | |
| ## 📥 Access & Download | |
| The data is split into `.tar` archives due to size. You can download them directly from the **[Files and versions](https://huggingface.co/datasets/Seba-san/AltoValleDataset/tree/main)** tab. | |
| ## ⚖️ Legal Notice & Citation | |
| The content of this database is under **Copyright** of the **Universidad Nacional del Comahue** and **INTA EEAV**. | |
| If you use this dataset in your research, please cite the work presented at **Jornadas Argentinas de Robótica (JAR) 2022**: | |
| * **Paper:** [Read PDF (Spanish)](https://github.com/Seba-san/AltoValleDataset/blob/main/AVD_v0.pdf) | |
| * **Video:** [Watch on YouTube](https://youtu.be/qrSIFyLzFrQ) | |
| ```bibtex | |
| @inproceedings{alto_valle_dataset_2022, | |
| title={Alto Valle Dataset: colección de datos experimentales enfocados en el estudio y desarrollo de algoritmos de navegación mediante visión en ambientes frutícolas}, | |
| author={Sansoni, Sebastian and Raverta Capua, Francisco and Moreyra, Marcelo L. and Benitez Piccini, Edgardo}, | |
| booktitle={Jornadas Argentinas de Robótica (JAR)}, | |
| year={2022}, | |
| organization={Universidad Nacional del Comahue & INTA EEAV}, | |
| url={https://github.com/Seba-san/AltoValleDataset} | |
| } | |
| ``` | |
| ## Acknowledgments | |
| This work was supported by the Project of Social Technological Development (PDTS) "Sistemas de Asistencia al Productor y Automatización de Máquinas para la Fruticultura de la Norpatagonia" (PDTS404), funded by CIN and CONICET. | |
| ``` | |