RINSE scores robot demonstration trajectories for smoothness via SAL and TED metrics to curate higher-quality data for behavioral cloning, improving success rates with less data on benchmarks and real robots.
Data quality in imitation learning,
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MSDP pretrains a transformer encoder via masked multisensory reconstruction and feeds the embeddings into an asymmetric actor-critic RL setup, yielding faster learning and high real-robot success rates with only 6,000 interactions.
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Learning from the Best: Smoothness-Driven Metrics for Data Quality in Imitation Learning
RINSE scores robot demonstration trajectories for smoothness via SAL and TED metrics to curate higher-quality data for behavioral cloning, improving success rates with less data on benchmarks and real robots.
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Self-Supervised Multisensory Pretraining for Contact-Rich Robot Reinforcement Learning
MSDP pretrains a transformer encoder via masked multisensory reconstruction and feeds the embeddings into an asymmetric actor-critic RL setup, yielding faster learning and high real-robot success rates with only 6,000 interactions.