1. Slug Mobile: Test-Bench for RL Testing
- Author
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Morris, Jonathan Wellington, Shah, Vishrut, Besanceney, Alex, Shah, Daksh, and Gilpin, Leilani H.
- Subjects
Computer Science - Robotics ,Computer Science - Machine Learning - Abstract
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., Comment: Submitted to BayLearn 2024
- Published
- 2024