Efficient and Robust Training of Dense Object Nets for Multi-Object Robot Manipulation
David B. Adrian,Andras Gabor Kupcsik,Markus Spies,Heiko Neumann,David B. Adrian,Andras Gabor Kupcsik,Markus Spies,Heiko Neumann
We propose a framework for robust and efficient training of Dense Object Nets (DON) [1] with a focus on industrial multi-object robot manipulation scenarios. DON is a popular approach to obtain dense, view-invariant object descriptors, which can be used for a multitude of downstream tasks in robot manipulation, such as, pose estimation, state representation for control, etc. However, the original ...
