Slug Mobile: Test-Bench for RL Testing
<|reference_start|>Slug Mobile: Test-Bench for RL Testing: Sim-to real gap in Reinforcement Learning is when a model trained in a simulator does not translate to the real world. This is a problem for Autonomous Vehicles (AVs) as vehicle dynamics can vary from simulation to reality, and also from vehicle to vehicle. Slug Mobile is a one tenth scale autonomous vehicle created to help address the sim-to-real gap for AVs by acting as a test-bench to develop models that can easily scale from one vehicle to another. In addition to traditional sensors found in other one tenth scale AVs, we have also included a Dynamic Vision Sensor so we can train Spiking Neural Networks running on neuromorphic hardware.<|reference_end|>
@article{morris2024slug,
    title={Slug Mobile: Test-Bench for RL Testing},
    author={Jonathan Wellington Morris, Vishrut Shah, Alex Besanceney, Daksh Shah,
  Leilani H. Gilpin},
    journal={arXiv preprint arXiv:2409.10532},
    year={2024},
    archivePrefix={arXiv},
    eprint={2409.10532},
    primaryClass={cs.RO cs.LG}
}