This repo contains the code for the paper, "From Navigation to Racing: Reward Signal Design for Autonomous Racing"

• We evaluate different reward signals on F1/10th autonomous cars
• We test the reward signals using a planning, perception and control navigation stack with a minimum curvature global planner and the Reference Modification local planner

• The repo contains two scripts to generate the results which are located in the TestingScripts folder
• The TrainVehicles.py Script will train the vehicles with the different reward signals
• The TestVehilces.py script, evaluated the vehicles.
• All the training and evaluation is done on the porto F1/10th race track.

• No racing reward
• Centerline progress reward
• Global plan progress reward
• Centerline cross-track, heading error reward
• Global plan cross-track, heading error reward
• Steering punishment reward

• Requirements:
  • PyTorch
  • Numpy
  • Matplotlib
  • casadi
  • numba
  • scipy
• Installation
  • clone the repo onto your computer
  • navigate into the folder, cd RewardSignalDesign
  • install it using pip python3 -m pip install -e .
• Built on Linux Ubuntu system (20.04.2 LTS) using Python v3.8.5

If you have found our work helpful, please cite as:

@inproceedings{evans2021reward,
  title={Reward signal design for autonomous racing},
  author={Evans, Benjamin and Engelbrecht, Herman A and Jordaan, Hendrik W},
  booktitle={2021 20th International Conference on Advanced Robotics (ICAR)},
  pages={455--460},
  year={2021},
  organization={IEEE}
}