This repository contains the source code of the paper Learning Tactile Models for Factor Graph-Based Estimation.
Install the pushestpy python package locally. In the push_estimation/pushestpy dir execute:
pip install -e .
Create a virtual python environment using Anaconda:
conda create -n env_push python=3.7
conda activate env_push
Install gtsam. Start by cloning the gtsam repository:
git clone https://github.com/borglab/gtsam.git
git checkout tags/4.0.0
Build and install the gtsam library:
cmake -DGTSAM_INSTALL_CYTHON_TOOLBOX=ON -DGTSAM_PYTHON_VERSION=3.7 ..
make -j
make install
If doing a local install, additionally pass in the install path -DCMAKE_INSTALL_PREFIX=../install.
Build and install the pushestcpp library for custom factors. In the push_estimation/ dir execute:
mkdir build/ && cd build/
cmake ..
make -j
make install
If you find this repository helpful in your publications, please cite the following:
@inproceedings{sodhi2021tactile,
title={Learning Tactile Models for Factor Graph-based Estimation},
author={Sodhi, Paloma and Kaess, Michael and Mukadam, Mustafa and Anderson, Stuart},
booktitle=IEEE Intl. Conf. on Robotics and Automation (ICRA),
year={2021},
}
This repository is licensed under the BSD License.