A binary-bottleneck model discovers object and action symbols from multi-modal effect predictions on random interactions, then uses discrete planning on predicted trajectories for tabletop repositioning and stacking with few-shot generalization to novel objects.
Neuro-symbolic robotics,
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Joint Discovery of Object and Action Symbols through Effect Prediction for Robotic Manipulation Planning
A binary-bottleneck model discovers object and action symbols from multi-modal effect predictions on random interactions, then uses discrete planning on predicted trajectories for tabletop repositioning and stacking with few-shot generalization to novel objects.