Integrating Symmetry into Differentiable Planning

@article{Zhao2022IntegratingSI,
  title={Integrating Symmetry into Differentiable Planning},
  author={Linfeng Zhao and Xu Zhu and Lingzhi Kong and Robin Walters and Lawson L. S. Wong},
  journal={ArXiv},
  year={2022},
  volume={abs/2206.03674}
}
We study how group symmetry helps improve data efficiency and generalization for end-to-end differentiable planning algorithms, specifically on 2D robotic path planning problems: navigation and manipulation. We first formalize the idea from Value Iteration Networks (VINs) on using convolutional networks for path planning, because it avoids explicitly constructing equivalence classes and enable endto-end planning. We then show that value iteration can always be represented as some convolutional… 
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