Optimal Solving of Constrained Path-Planning Problems with Graph Convolutional Networks and Optimized Tree Search

@article{Osanlou2019OptimalSO,
  title={Optimal Solving of Constrained Path-Planning Problems with Graph Convolutional Networks and Optimized Tree Search},
  author={Kevin Osanlou and Andrei Bursuc and Christophe Guettier and Tristan Cazenave and {\'E}ric Jacopin},
  journal={2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
  year={2019},
  pages={3519-3525}
}
Learning-based methods are growing prominence for planning purposes. However, there are very few approaches for learning-assisted constrained path-planning on graphs, while there are multiple downstream practical applications. This is the case for constrained path-planning for Autonomous Unmanned Ground Vehicles (AUGV), typically deployed in disaster relief or search and rescue applications. In off-road environments, the AUGV must dynamically optimize a source-destination path under various… 

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