Experiments from "Certifiably Correct Range-Aided SLAM"
We packaged a working conda
environment which handles most of the
dependencies. However, there are a few repos that you will need to install
manually as of now. The below snippet should get you started.
# clone the repo
cd ~
git clone git@github.com:MarineRoboticsGroup/cora-experiments.git
# create a conda environment from environment.yml
cd cora-experiments
conda env create -f environment.yml
conda activate cora
# install other dependencies
cd ~
git clone git@github.com:MarineRoboticsGroup/cora.git # CORA (MATLAB)
git clone git@github.com:MarineRoboticsGroup/PyFactorGraph.git # PyFactorGraph (Python) - to hold problems
git clone git@github.com:MarineRoboticsGroup/gtsam-range-aided-slam.git # our GTSAM-based solver (Python)
cd ~/PyFactorGraph; pip install -e . # install PyFactorGraph
cd ~/gtsam-range-aided-slam; pip install -e . # install our GTSAM solver
# optional (only for Manhattan experiments)
cd ~
git clone git@github.com:MarineRoboticsGroup/manhattan-world-sim.git
cd ~/manhattan-world-sim; pip install -e . # install manhattan-world-sim
The different experiments are all inside our experiments/
directory. You
should be able to run any of the scripts to recreate the results in our paper.