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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2409.10532 |
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| _version_ | 1866910861930528768 |
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| author | Morris, Jonathan Wellington Shah, Vishrut Besanceney, Alex Shah, Daksh Gilpin, Leilani H. |
| author_facet | Morris, Jonathan Wellington Shah, Vishrut Besanceney, Alex Shah, Daksh Gilpin, Leilani H. |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_10532 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Slug Mobile: Test-Bench for RL Testing Morris, Jonathan Wellington Shah, Vishrut Besanceney, Alex Shah, Daksh Gilpin, Leilani H. Robotics Machine Learning 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. |
| title | Slug Mobile: Test-Bench for RL Testing |
| topic | Robotics Machine Learning |
| url | https://arxiv.org/abs/2409.10532 |