We present the Grasp Proposal Network (GP-net), a Convolutional Neural Network model which can generate 6-DOF grasps for mobile manipulators. To train GP-net, we synthetically generate a dataset containing depth-images and ground-truth grasp information for more than 1400 objects. We use the EGAD! grasping benchmark to evaluate GP-net against two commonly used algorithms, the Volumetric Grasping Network (VGN) and the Grasp Pose Detection package (GPD), on a PAL TIAGo mobile manipulator in real-world experiments. GP-net achieves grasp success rates of 82.2% compared to 57.8% for VGN and 63.3% with GPD. In contrast to the state-of-the-art methods in robotic grasping, GP-net can be used out-of-the-box for grasping objects with mobile manipulators without limiting the workspace, requiring table segmentation or needing additional hardware like high-end GPUs.
This work is currently under review.
The data for training, dataset generation and pre-trained models are available on zenodo. If you want to use the ROS package on your robot without any model training, use gpnet-ros. If you want to train a new model, use the GP-net repository. If you want to train a model for an alternative gripper, use this code based on DexNet to generate a new dataset
If you use our code, please cite
A. Konrad, J. McDonald and R. Villing, “Proposing Grasps for Mobile Manipulators,” in review.
along with
J. Mahler, J. Liang, S. Niyaz, M. Laskey, R. Doan, X. Liu, J. A. Ojea, and K. Goldberg, “Dex-net 2.0: Deep learning to plan robust grasps with synthetic point clouds and analytic grasp metrics,” in Robotics: Science and Systems (RSS), 2017.
and
M. Breyer, J. J. Chung, L. Ott, S. Roland, and N. Juan, “Volumetric grasping network: Real-time 6 dof grasp detection in clutter,” in Conference on Robot Learning, 2020
Acknowledgements
This publication has emanated from research supported in part by Grants from Science Foundation Ireland under Grant numbers 18/CRT/6049 and 16/RI/3399. The opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the Science Foundation Ireland.
Contact
If you’re having questions about any of our projects, please contact Anna Konrad, Prof. John McDonald or Dr. Rudi Villing.