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Register a new userImproved GQ-CNN: Deep Learning Model for Planning Robust Grasps
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Jakub \\'Swi\\k{a}tkowski
Publication date
2018
fields
Informatics Engineering
and research's language is
English
Authors
Maciej Jaskowski
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Recent developments in the field of robot grasping have shown great improvements in the grasp success rates when dealing with unknown objects. In this work we improve on one of the most promising approaches, the Grasp Quality Convolutional Neural Network (GQ-CNN) trained on the DexNet 2.0 dataset. We propose a new architecture for the GQ-CNN and describe practical improvements that increase the model validation accuracy from 92.2% to 95.8% and from 85.9% to 88.0% on respectively image-wise and object-wise training and validation splits.
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