Segmentation for Grasping: A Holistic Framework for Autonomous Table Clearing

Author:

Chung Ka-Shing,Ang Marcelo H.,Lin Wei,Zhu Haiyue,Short Joel,Tao Pey Yuen

Publisher

Springer Nature Switzerland

Reference13 articles.

1. Sundermeyer, M., Mousavian A., Triebel, R., Fox, D.: Contact-GraspNet: efficient 6-DoF grasp generation in cluttered scenes. In: IEEE International Conference on Robotics and Automation (2021)

2. ten Pas, A., Gualtieri, M., Saenko, K., Platt, R.: Grasp pose detection in point clouds. Int. J. Robot. Res. 36(13–14), 1455–1473 (2017)

3. Minghao, G., Hao-Shu, F., Zhanda, Z., Sheng, X., Chenxi, W., Cewu, L.: RGB matters: learning 7-DoF grasp poses on monocular RGBD images. In: IEEE International Conference on Robotics and Automation (2021)

4. Hao-Shu, F., Chenxi, W., Minghao, G., Cewu, L.: GraspNet-1Billion: a large-scale benchmark for general object grasping. In: IEEE Conference on Computer Vision and Pattern Recognition (2020)

5. He, K., Gkioxari, G., Dollár, P., Girshick, R.: Mask R-CNN. In: IEEE International Conference on Computer Vision (2017)

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