Transferring Experience from Simulation to the Real World for Precise Pick-And-Place Tasks in Highly Cluttered Scenes
Kilian Kleeberger,Markus Völk,Marius Moosmann,Erik Thiessenhusen,Florian Roth,Richard Bormann,Marco F. Huber,Kilian Kleeberger,Markus Völk,Marius Moosmann,Erik Thiessenhusen,Florian Roth,Richard Bormann,Marco F. Huber
In this paper, we introduce a novel learning-based approach for grasping known rigid objects in highly cluttered scenes and precisely placing them based on depth images. Our Placement Quality Network (PQ-Net) estimates the object pose and the quality for each automatically generated grasp pose for multiple objects simultaneously at 92 fps in a single forward pass of a neural network. All grasping ...
