A transformer policy distilled from a privileged RL teacher enables 3.1x faster real-world cube rotation on the ORCA hand using solely joint sensor data by extracting implicit object state from temporal joint patterns.
Learning quadrupedal locomotion over challenging terrain
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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cs.RO 2years
2026 2representative citing papers
Concurrent training of an Intrinsic Dynamics Head with a dynamics reward yields more efficient and smoother quadrupedal locomotion policies that transfer to real robots with 12-18% gains in efficiency metrics.
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Learning Robust Dexterous In-Hand Manipulation from Joint Sensors with Proprioceptive Transformer
A transformer policy distilled from a privileged RL teacher enables 3.1x faster real-world cube rotation on the ORCA hand using solely joint sensor data by extracting implicit object state from temporal joint patterns.