Deep Learning for Detecting Robotic Grasps Deep Learning for Detecting Robotic Grasps
Paper summary this paper uses the common 2-step procedure to first eliminate most of unlikely detection windows (high recall), then use a network with higher capacity for better discrimination (high precision). Deep learning (in the unsupervised sense) helps having features optimized for each of these 2 different tasks, adapt them for different situations (different robotics grippers) and beat hand-designed features for detection of graspable areas, using a mixture of inputs (depth + rgb + xyz).
arxiv.org
scholar.google.com
Deep Learning for Detecting Robotic Grasps
Lenz, Ian and Lee, Honglak and Saxena, Ashutosh
arXiv e-Print archive - 2013 via Bibsonomy
Keywords: dblp


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