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Deep learning for detecting robotic grasps
2015
The international journal of robotics research
We consider the problem of detecting robotic grasps in an RGB-D view of a scene containing objects. In this work, we apply a deep learning approach to solve this problem, which avoids time-consuming hand-design of features. This presents two main challenges. First, we need to evaluate a huge number of candidate grasps. In order to make detection fast and robust, we present a two-step cascaded system with two deep networks, where the top detections from the first are re-evaluated by the second.
doi:10.1177/0278364914549607
fatcat:vgo22gpforgb5mtyi4ogl27eny