Planning to monitor wildfires with a fleet of UAVs
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README.md

FireRS Situation Assessment and Observation Planning

FireRS Situation Assessment and Observation Planning (SAOP) is composed of several python modules:

  • geodata: geographic and environmental data manipulation
  • firemodel: wildfire propagation
  • planning: high-level interface for UAV planning

and a C++ library (libsaop) with python interfaces:

Running SAOP

Build Status

Requirements

A GNU/Linux operating system with:

  • cmake
  • a C++11 compiler (at least)
  • Boost
  • python 3.5
  • Cython
  • pybind11
  • gdal
  • windninja
  • The following python packages:
    • affine
    • GDAL
    • joblib
    • matplotlib
    • numpy
    • pybind11
    • pytz
    • scikit-image
    • ...

Optionally:

  • Neptus and Dune for UAV simulation and plan execution

The file docker/Dockerfile contains all the steps require to retrieve all dependencies on an Ubuntu 16.04 distribution.

pybind11 is present as a submodule of the current repository. To retrieve it:

git submodule init
git submodule update

On your system

Just do make build.

In detail, targets for the Makefile are:

  • build: compile the project (default target)
  • build-debug: compile libsaop with debugging symbols
  • build-testing: compile including libsaop tests with debugging symbols in the build
  • autobuild: recompile the project each time a source file is changed (requires "when-changed")
  • benchmark: Create a random fire scenario and benchmark observation plan search.
  • doc: generate libsaop python interface html documentation
  • clean: remove the build folder and python artifacts
  • test-python: run all python unit tests
  • test-cpp: run unittests specific to the C++ module only
  • test-python-cpp: run test interfacing the python and C++ codes.
  • docker: starts a shell in the docker container.
  • docker_build_container: Build/rebuild the docker image.

Additionally, SAOP cmake build can be configured manually with:

mkdir build/
cd build
cmake ..
make

This process will:

  • build a C++ backend with python bindings
  • build the Cython modules in python/
  • ensure that the produced artifacts are located in the python/ source directory so that the python scripts can be invoke in straightforward manner.

On Docker

A Dockerfile is provided to set up an environment with windninja and all python dependencies.

To build the container:

./docker/run.sh build

To start a shell in the container with the the code repository and the data repository mounted:

./docker/run.sh [start]