Researchers developed EMBODIEDSWE-BENCH, a simulation benchmark for coding agents that spans contact-rich manipulation and deformable object tasks in long-horizon, dexterous robotics, to test whether agent-generated solutions can provide scalable supervision for learning general robot policies. The work studies coding agents specifically for long-horizon dexterous robotics.
We study coding agents for long-horizon, dexterous robotics and ask whether their solutions can provide scalable supervision for learning general robot policies. To test this, we develop EMBODIEDSWE-BENCH, a simulation benchmark for coding agents spanning contact-rich manipulation, deformable object
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