Fusion of neural networks, for LIDAR-based evidential road mapping

@article{Capellier2021FusionON,
  title={Fusion of neural networks, for LIDAR-based evidential road mapping},
  author={Edouard Capellier and Franck Davoine and V{\'e}ronique Berge-Cherfaoui and You Li},
  journal={J. Field Robotics},
  year={2021},
  volume={38},
  pages={727-758}
}
LIDAR sensors are usually used to provide autonomous vehicles with 3D representations of their environment. In ideal conditions, geometrical models could detect the road in LIDAR scans, at the cost of a manual tuning of numerical constraints, and a lack of flexibility. We instead propose an evidential pipeline, to accumulate road detection results obtained from neural networks. First, we introduce RoadSeg, a new convolutional architecture that is optimized for road detection in LIDAR scans… Expand

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