Deep 6-DoF Tracking of Unknown Objects for Reactive Grasping
Marc Tuscher, Julian Hörz, Danny Driess, Marc Toussaint
Abstract
Robotic manipulation of unknown objects is an important field of research. Practical applications occur in many real-world settings where robots need to interact with an unknown environment. We tackle the problem of reactive grasping by proposing a method for unknown object tracking, grasp point sampling and dynamic trajectory planning. Our object tracking method combines Siamese Networks with an Iterative Closest Point approach for pointcloud registration into a method for 6-DoF unknown object tracking. The method does not require further training and is robust to noise and occlusion. We propose a robotic manipulation system, which is able to grasp a wide variety of formerly unseen objects and is robust against object perturbations and inferior grasping points.
BibTeX
@inproceedings{icra2021_deep6doftracking,
title = {Deep 6-DoF Tracking of Unknown Objects for Reactive Grasping},
author = {Marc Tuscher and Julian Hörz and Danny Driess and Marc Toussaint},
booktitle = {ICRA 2021},
year = {2021}
}