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Learning Sampling Dictionaries for Efficient and Generalizable Robot Motion Planning with Transformers
Stage 1 is a Vector Quantized-Variational AutoEncoder model that learns to represent the planning space using a finite number of sampling distributions, and stage 2 is an Auto-Regressive model that constructs a sampling region for SMPs by selecting from the learned sampling distribution sets.
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