FieldSAFE - Dataset for Obstacle Detection in Agriculture

This repository contains the necessary software for utilizing the FieldSAFE dataset. Software and example usage scripts are available in the folder "ros". Further, ground truth GPS annotations for all static and dynamic obstacles are contained in the folder "ground_truth".

For more information, visit the FieldSAFE website: https://vision.eng.au.dk/fieldsafe/

Citation

If you use this dataset in your research or elsewhere, please cite/reference the following paper:

FieldSAFE: Dataset for Obstacle Detection in Agriculture

@article{kragh2017fieldsafe,
  title={FieldSAFE: Dataset for Obstacle Detection in Agriculture},
  author={Kragh, Mikkel Fly and Christiansen, Peter and Laursen, Morten Stigaard and Larsen, Morten and Steen, Kim Arild and Green, Ole and Karstoft, Henrik and J{\o}rgensen, Rasmus Nyholm},
  journal={arXiv preprint arXiv:1709.03526},
  year={2017}
}

Installation Instructions

The FieldSAFE dataset and software has been tested with Ubuntu 16.04 and ROS Kinetic, but may work with other Linux distributions and newer ROS distributions. Below, installations instructions for all necessary dependencies are given.

Install ROS Kinetic on Ubuntu 16.04 (Desktop-Full Install)

http://wiki.ros.org/kinetic/Installation/Ubuntu

Install the following additional packages:

sudo apt-get install ros-kinetic-robot-localization 
sudo apt-get install ros-kinetic-geographic-msgs
sudo apt-get install libpcap-dev

Clone and build this repository

git clone https://github.com/mikkelkh/FieldSAFE
cd FieldSAFE
git submodule update --init --recursive
cd ros
catkin_make

Environment Setup
```
source devel/setup.bash
```
Download a 1 minute example bag with sensor data:

2016-10-25-11-41-21_example.bag

Run the demo

roslaunch demo demo.launch file:=/path/to/2016-10-25-11-41-21_example.bag

Download more data from:

https://vision.eng.au.dk/fieldsafe/

tambetm/FieldSAFE

FieldSAFE - Dataset for Obstacle Detection in Agriculture

Citation

Installation Instructions