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Zhao, Linfeng ; Zhu, Xupeng ; Kong, Lingzhi ; Waltes, Robin ; Wong, Lawson LS ( , International Conference on Learning Representations)To achieve this, we draw inspiration from equivariant convolution networks and model the path planning problem as a set of signals over grids. We demonstrate that value iteration can be treated as a linear equivariant operator, which is effectively a steerable convolution. Building upon Value Iteration Networks (VIN), we propose a new Symmetric Planning (SymPlan) framework that incorporates rotation and reflection symmetry using steerable convolution networks. We evaluate our approach on four tasks: 2D navigation, visual navigation, 2 degrees of freedom (2-DOF) configuration space manipulation, and 2-DOF workspace manipulation. Our experimental results show that our symmetric planning algorithms significantly improve training efficiency and generalization performance compared to non-equivariant baselines, including VINs and GPPN.more » « less
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Zhao, Linfeng ; Kong, Lingzhi ; Walters, Robin ; Wong, Lawson L.S. ( , International Conference on Machine Learning)
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Kong, Lingzhi ; Zhang, Peng ; Li, Wang ; Yang, Yan ; Tian, Ye ; Wang, Xujun ; Chen, Sujun ; Yang, Yuxin ; Huang, Tianhao ; Zhao, Tian ; et al ( , Oncotarget)