Agronav: Autonomous Navigation Framework for Agricultural Robots and Vehicles Using Semantic Segmentation and Semantic Line Detection

Abstract

The successful implementation of vision-based navigation in agricultural fields hinges upon two critical components: 1) the accurate identification of key components within the scene, and 2) the identification of lanes through the detection of boundary lines that separate the crops from the traversable ground. We propose Agronav, an end-to-end vision-based autonomous navigation framework, which outputs the centerline from the input image by sequentially processing it through semantic segmentation and semantic line detection models. We also present Agroscapes, a pixel-level annotated dataset collected across six different crops, captured from varying heights and angles. This ensures that the framework trained on Agroscapes is generalizable across both ground and aerial robotic platforms. Codes, models and dataset will be released at github.com/shivamkumarpanda/agronav.

Cite

Text

Panda et al. "Agronav: Autonomous Navigation Framework for Agricultural Robots and Vehicles Using Semantic Segmentation and Semantic Line Detection." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2023. doi:10.1109/CVPRW59228.2023.00667

Markdown

[Panda et al. "Agronav: Autonomous Navigation Framework for Agricultural Robots and Vehicles Using Semantic Segmentation and Semantic Line Detection." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2023.](https://mlanthology.org/cvprw/2023/panda2023cvprw-agronav/) doi:10.1109/CVPRW59228.2023.00667

BibTeX

@inproceedings{panda2023cvprw-agronav,
  title     = {{Agronav: Autonomous Navigation Framework for Agricultural Robots and Vehicles Using Semantic Segmentation and Semantic Line Detection}},
  author    = {Panda, Shivam Kumar and Lee, Yongkyu and Jawed, Mohammad Khalid},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
  year      = {2023},
  pages     = {6272-6281},
  doi       = {10.1109/CVPRW59228.2023.00667},
  url       = {https://mlanthology.org/cvprw/2023/panda2023cvprw-agronav/}
}