Robust and efficient coverage paths for autonomous agricultural vehicles
The extended documentation is here.
The coverage path planning problem (CPP) aims to create a path to cover an area with one or several vehicles. CPP has many application as cleaning robots, surveillance, de-mining or agriculture. Each of the application has its own requirements. For example, in cleaning robots environment is usually unknown and the objective is improve the probability of cover the area. On the other hand, CPP in agriculture knows the area to cover, but the coverage has to be complete.
Fields2Cover library provides several algorithms to plan the coverage path on any kind of fields:
Although the development of this project is focused on offline planning of agricultural vehicles, the library accepts pull requests from other types of coverage planners.
The version 2.0 of Fields2Cover comes with support for non-convex fields and fields with obstacles!! This has been huge request from the community and finally it's here.
A quick list of new additions to the library:
- Decomposition algorithms:
- Trapezoidal and Boustrophedon decomposition. Those algorithms are useful to split any concave field into several convex sub-fields.
- Route planner:
- Route optimizer using OR-tools can be used to order the swaths, instead of just using a known pattern.
- Support for a point used as the start and end points of the route.
- Path planner:
- Support for routes provided by the route optimizer.
- Swath generator:
- Speed improvement on swath generation.
- New cost function: NSwathModified. It uses an approximation to compute the number of swaths, reducing computation costs.
- Many bugs fixed.
Please cite the following paper (https://ieeexplore.ieee.org/document/10050562) when using Fields2Cover for your research:
@article{Mier_Fields2Cover_An_open-source_2023,
author={Mier, Gonzalo and Valente, João and de Bruin, Sytze},
journal={IEEE Robotics and Automation Letters},
title={Fields2Cover: An Open-Source Coverage Path Planning Library for Unmanned Agricultural Vehicles},
year={2023},
volume={8},
number={4},
pages={2166-2172},
doi={10.1109/LRA.2023.3248439}
}
There are many CPP papers out there, but almost no code about their implementation. Due to this, research about this topic is slow as you need to implement every algorithm you want to compare with.
Fields2Cover provides a flexible structure and several algorithms to compare with, so any developer can research about this topic easily.
The Fields2Cover package has only been tested on Ubuntu 18.04, 20.04 and 22.04. If you are able to run it in other operative systems, open an issue/PR and it will be added to this guide
Some packages are needed before compiling the package:
📝
If your OS is Ubuntu 18.04 or 20.04, you would need to dosudo add-apt-repository ppa:ubuntugis/ppa
sudo apt-get update
sudo apt-get install --no-install-recommends software-properties-common
sudo add-apt-repository ppa:ubuntugis/ppa
sudo apt-get update
sudo apt-get install --no-install-recommends build-essential ca-certificates cmake \
doxygen g++ git libeigen3-dev libgdal-dev libpython3-dev python3 python3-pip \
python3-matplotlib python3-tk lcov libgtest-dev libtbb-dev swig libgeos-dev \
gnuplot libtinyxml2-dev nlohmann-json3-dev
python3 -m pip install gcovr
Also, OR-tools for C++ is needed. Follow its installation process.
First, clone this repository. Then, from the source code folder of the project:
mkdir -p build;
cd build;
cmake -DCMAKE_BUILD_TYPE=Release -DUSE_ORTOOLS_RELEASE=ON ..;
make -j$(nproc);
Finally, you can install it as:
sudo make install;
To add Fields2Cover into your CMakeLists.txt, it is as easy as:
find_package(Fields2Cover REQUIRED)
target_link_libraries(<<<your_package>>> Fields2Cover)
Assuming you have satisfied the "Requirements on Linux" and completed the initial "Compilation" step.
Install the packages required as:
sudo apt install swig python3-pytest
Then, from the source code folder of the project, adjust the BUILD_PYTHON option of the existing build:
cd build;
cmake -DBUILD_PYTHON=ON ..;
make -j$(nproc);
sudo make install;
To test if the compilation and installation of the python interface is correct, run on python:
import fields2cover
Or run on the main folder:
pytest-3 tests/python/
Fields2Cover is still in early development, so feedback and bug reports are appreciated. At the moment, it should expected that breaking changes may be introduced as new functionality is added, bugs are fixed, and APIs are streamlined.
If you find any issue/bug/proposal, open an issue and we will try to solve/discuss it.
Pull requests are more than welcome. For major changes, please open an issue first to discuss what you would like to change. Please make sure to update tests as appropriate.
Contributions can be easily made using
Fields2Cover project is under BSD-3 license.
- Support small obstacles
- Headland coverage
- Create SWIG interface with Lua/R
- ...
This library is only possible thanks to GDAL who provides the basic types of this library. Other great libraries that made Fields2Cover possible are OR-tools, hbanzhaf/steering_functions, nlohmann/json, leethomason/tinyxml2, ttk592/spline and alandefreitas/matplotplusplus
This code repository is part of the project Fields2Cover which is (partly) financed by the Dutch Research Council (NWO).