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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/2410.07209 |
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| _version_ | 1866914969075843072 |
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| author | Moraes, Pablo Peters, Christopher Sodre, Hiago Moraes, William Barcelona, Sebastian Deniz, Juan Castelli, Victor Guterres, Bruna Grando, Ricardo |
| author_facet | Moraes, Pablo Peters, Christopher Sodre, Hiago Moraes, William Barcelona, Sebastian Deniz, Juan Castelli, Victor Guterres, Bruna Grando, Ricardo |
| contents | This article presents the implementation and evaluation of a behavior cloning approach for route following with autonomous cars. Behavior cloning is a machine-learning technique in which a neural network is trained to mimic the driving behavior of a human operator. Using camera data that captures the environment and the vehicle's movement, the neural network learns to predict the control actions necessary to follow a predetermined route. Mini-autonomous cars, which provide a good benchmark for use, are employed as a testing platform. This approach simplifies the control system by directly mapping the driver's movements to the control outputs, avoiding the need for complex algorithms. We performed an evaluation in a 13-meter sizer route, where our vehicle was evaluated. The results show that behavior cloning allows for a smooth and precise route, allowing it to be a full-sized vehicle and enabling an effective transition from small-scale experiments to real-world implementations. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_07209 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Behavior Cloning for Mini Autonomous Car Path Following Moraes, Pablo Peters, Christopher Sodre, Hiago Moraes, William Barcelona, Sebastian Deniz, Juan Castelli, Victor Guterres, Bruna Grando, Ricardo Robotics This article presents the implementation and evaluation of a behavior cloning approach for route following with autonomous cars. Behavior cloning is a machine-learning technique in which a neural network is trained to mimic the driving behavior of a human operator. Using camera data that captures the environment and the vehicle's movement, the neural network learns to predict the control actions necessary to follow a predetermined route. Mini-autonomous cars, which provide a good benchmark for use, are employed as a testing platform. This approach simplifies the control system by directly mapping the driver's movements to the control outputs, avoiding the need for complex algorithms. We performed an evaluation in a 13-meter sizer route, where our vehicle was evaluated. The results show that behavior cloning allows for a smooth and precise route, allowing it to be a full-sized vehicle and enabling an effective transition from small-scale experiments to real-world implementations. |
| title | Behavior Cloning for Mini Autonomous Car Path Following |
| topic | Robotics |
| url | https://arxiv.org/abs/2410.07209 |