Autonomously Acquiring Robot Manipulation Skills with Language-Driven Quality-Diversity
This paper proposes an approach designed to output diverse motion primitive archives by autonomously leveraging quality-diversity algorithms, only requiring a free-form description of the task in common language, and proposes an autonomous exploration mechanism able to reliably output sets of functionals covering the f...