Oct 23, 2019 · We introduce an end-to-end method that represents targetable visuomotor skills as a goal-parameterized neural network policy.

Oct 23, 2019 · We introduce an end-to-end method that represents targetable visuomotor skills as a goal-parameterized neural network policy. By training on an ...

Code repository for the paper "Learning Deep Parameterized Skills for Re-Targetable Visuomotor Control" by the H2R Lab in collaboration with MERL. Read the ...

Nov 26, 2019 · Learning Deep Parameterized Skills from. Demonstration for Re-targetable Visuomotor Control. Technical report, 2019. Chelsea Finn, Tianhe Yu ...

Learning deep parameterized skills from demonstration for re-targetable visuomotor control. J Chang, N Kumar, S Hastings, A Gokaslan, D Romeres, D Jha ...

We introduce an end-to-end method for targetable visuomotor skills as a goal-parameterized neual network policy, resulting in successfully learning a mapping ...

We introduce an end-to-end method that represents targetable visuomotor skills as a goal-parameterized neural network policy. By training on an informative ...

... Learning Deep Parameterized Skills from Demonstration for Re-targetable Visuomotor Control | Robots need to learn skills that can not only generalize across ...

A sample-efficient method for constructing reusable parameterized skills that can solve families of related motor tasks and proposes a method for reusing ...

Learning Deep Parameterized Skills from Demonstration for Re-targetable Visuomotor Control ... We demonstrate that our model trained on 33% of the possible goals ...