Multi-task Domain Adaptation for Deep Learning of Instance Grasping from Simulation

ICRA, 2018.

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Abstract:

Learning-based approaches to robotic manipulation are limited by the scalability of data collection and accessibility of labels. In this paper, we present a multi-task domain adaptation framework for instance grasping in cluttered scenes by utilizing simulated robot experiments. Our neural network takes monocular RGB images and the instan...More

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