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fire-rs-saop repositorypython docker cmake uav cpp gis fleet wildfire vns observation-planning situation-assessment |
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fire-rs-saop repositorypython docker cmake uav cpp gis fleet wildfire vns observation-planning situation-assessment |
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fire-rs-saop repositorypython docker cmake uav cpp gis fleet wildfire vns observation-planning situation-assessment |
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fire-rs-saop repositorypython docker cmake uav cpp gis fleet wildfire vns observation-planning situation-assessment |
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fire-rs-saop repositorypython docker cmake uav cpp gis fleet wildfire vns observation-planning situation-assessment supersaop |
Repository Summary
Description | Planning to monitor wildfires with a fleet of UAVs |
Checkout URI | https://github.com/laas/fire-rs-saop.git |
VCS Type | git |
VCS Version | master |
Last Updated | 2021-07-09 |
Dev Status | UNKNOWN |
Released | UNRELEASED |
Tags | python docker cmake uav cpp gis fleet wildfire vns observation-planning situation-assessment |
Contributing |
Help Wanted (-)
Good First Issues (-) Pull Requests to Review (-) |
Packages
Name | Version |
---|---|
supersaop | 0.0.0 |
README
FireRS Situation Assessment and Observation Planning
FireRS Situation Assessment and Observation Planning (SAOP) is a software for planning, execution and supervision of wildfire monitoring missions with fleets of UAVs.
FireRS SAOP is composed of several python packages:
-
fire_rs.geodata
: geographic and environmental data manipulation -
fire_rs.firemodel
: wildfire propagation -
fire_rs.planning
: high-level interface for UAV planning -
fire_rs.monitoring
: high-level functionalities of the wildfire monitoring mission -
fire_rs.simulation
: create and control a synthetic wildfire in the Morse robotic simulator
*Those can be found in the
``` directory.*
A C++ library (___libsaop___) implementing:
- A VNS-based observation planning algorithm for wildfire monitoring.
- The communication with [Neptus](https://github.com/LSTS/neptus) and [Dune](https://github.com/LSTS/dune) software for the operation of unmanned vehicles.
- A trivial wildfire mapping algorithm.
The functionality provided by _libsaop_ is also exposed trough three python interfaces:
- *uav_planning*: Core planning algorithm
- *neptus*: Communication with Neptus and Dune
- *firemapping*: mapping algorithms
And a ROS package (___supersaop___) for real time execution of SAOP with real or simulated UAVs in a real or synthetic wildfire scenario.
## SAOP environment setup
### 1. On Docker
The easiest way to start with SAOP is using docker.
To build the container:
./docker/run.bash build
The file `docker/Dockerfile` contains all the steps to build a SAOP-ready Ubuntu 18.04 image.
To start a shell in the container with the the code repository and the data repository mounted:
./docker/run.bash start
The `/docker/run.bash` is the recommended way to build and run the SAOP docker container as it sets up some X11 bindings from the host.
### 2. Local software requirements
_(If you are using docker, skip this section and continue with **Geographic data**)_
The core functions of FireRS SAOP require running a GNU/Linux operating system (Ubuntu 18.04 and Fedora 29 tested) with:
- cmake
- a C++11 compiler
- Boost
- python 3.5
- Cython
- OpenCV
- [pybind11](https://github.com/pybind/pybind11/)
- gdal
- [windninja](https://github.com/firelab/windninja)
- The following python packages:
* affine
* cv2
* GDAL
* joblib
* matplotlib
* numpy
* pandas
* pybind11
* pytz
* scikit-image
* scipy
* six
Using Ubuntu, run as *root*:
apt install g++ cmake python3 cython3 python3-gdal python3-setuptools\
python3-pip python3-affine python3-tz python3-pandas python3-numpy\
python3-matplotlib libboost-all-dev libgdal-dev libopencv-shape\
python3-opencv
pip3 install pybind11 joblib scikit-image scipy
*pybind11 is present as a submodule of the current repository. To retrieve it:*
git submodule init
git submodule update
#### 3.1 Real time execution requirements
Optionally, for the real time execution:
- [ROS](http://www.ros.org/)
- [Neptus](https://github.com/lsts/neptus) and [Dune](https://github.com/lsts/dune)
### 3. Geographic data
On top of the software requierements, some geographic data are needed in order to propagate a fire in the area of your choice.
You should set an environment variable
```FIRERS_DATA
``` containing the path to a folder with 3 folders inside following this structure:
-
```firers_data/
File truncated at 100 lines see the full file
CONTRIBUTING
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fire-rs-saop repositorypython docker cmake uav cpp gis fleet wildfire vns observation-planning situation-assessment |
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