This is the documentation for F1TENTH's Autonomous Racing Software Stack. The stack will be split into three main topics: Perception, Planning, and Control. We'll try to include all software algorithms we've encountered, tested, and used in our research in Autonomous Racing. This repo is constantly being updated. If you have algorithms that you've used in your Autonomous Racing applications and wish to make it open source, please consider :ref:`contribute <doc_contribution_guide>` to this repo.
GitHub repo to the source code: https://github.com/f1tenth/f1tenth_planning
If you use any open source implementations mentioned in this repo NOT authored by us, please cite the original authors and give proper credits. All original author information will be included in the documentation if not authored by us.
Otherwise, if you find this repo helpful in your work, please consider citing:
@inproceedings{o2020textscf1tenth, title={textscF1TENTH: An Open-source Evaluation Environment for Continuous Control and Reinforcement Learning}, author={O’Kelly, Matthew and Zheng, Hongrui and Karthik, Dhruv and Mangharam, Rahul}, booktitle={NeurIPS 2019 Competition and Demonstration Track}, pages={77--89}, year={2020}, organization={PMLR} }
Hongrui Zheng: hongruiz AT seas DOT upenn DOT edu
Johannes Betz: joebetz AT seas DOT upenn DOT edu
.. toctree:: :maxdepth: 1 :caption: Perception :name: sec-perception :hidden: perception/particle_filter
.. toctree:: :maxdepth: 1 :caption: Planning :name: sec-planning :hidden: planning/wall_follow planning/fgm planning/lane_switcher planning/lattice_planner planning/graph_planner
.. toctree:: :maxdepth: 1 :caption: Control :name: sec-control :hidden: control/pure_pursuit control/stanley control/lqr control/kinematic_mpc
.. toctree:: :maxdepth: 1 :caption: Contributing :name: sec-contribute :hidden: contribute