We present the Versatile Grasp Quality Convolutional Neural Network (VGQ-CNN), a grasp quality prediction network for 6-DOF grasps. VGQ-CNN can be used when evaluating grasps for objects seen from a wide range of camera poses or mobile robots without the need to retrain the network. By defining the grasp orientation explicitly as an input to the network, VGQ-CNN can evaluate 6-DOF grasp poses, moving beyond the 4-DOF grasps used in most image-based grasp evaluation methods like GQ-CNN. We train VGQ-CNN on our new Versatile Grasp dataset (VG-dset), containing 6-DOF grasps observed from a wide range of camera poses. VGQ-CNN achieves a balanced accuracy of 82.1% on our test-split while generalising to a variety of camera poses. Meanwhile, it achieves competitive performance for overhead cameras and top-grasps with a balanced accuracy of 74.2% compared to GQ-CNN’s 76.6%. We also propose a modified network architecture, Fast-VGQ-CNN, that speeds up inference using a shared encoder architecture and can make 128 grasp quality predictions in 12ms on a CPU.

This work has been accepted for the International Joint Conference on Neural Networks (IJCNN) 2022.

Our code and our data can be accessed here.

If you use our code, please cite

A. Konrad, J. McDonald and R. Villing, “VGQ-CNN: Moving beyond fixed cameras and top-grasps for grasp quality prediction,” to appear in International Joint Conference on Neural Networks (IJCNN), 2022.

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.

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.