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Deep 6-DoF Tracking of Unknown Objects for Reactive Grasping

2021-03-09 12:51:17
Marc Tuscher, Julian Hörz, Danny Driess, Marc Toussaint
arXiv_AI
       
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.

Abstract (translated)

URL

https://arxiv.org/abs/2103.05401

PDF

https://arxiv.org/pdf/2103.05401.pdf

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