Deep learning approaches to grasp synthesis: A review

R Newbury, M Gu, L Chumbley… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
Gras** is the process of picking up an object by applying forces and torques at a set of
contacts. Recent advances in deep learning methods have allowed rapid progress in robotic …

Vision-based robotic gras** from object localization, object pose estimation to grasp estimation for parallel grippers: a review

G Du, K Wang, S Lian, K Zhao - Artificial Intelligence Review, 2021 - Springer
This paper presents a comprehensive survey on vision-based robotic gras**. We
conclude three key tasks during vision-based robotic gras**, which are object localization …

Pointr: Diverse point cloud completion with geometry-aware transformers

X Yu, Y Rao, Z Wang, Z Liu, J Lu… - Proceedings of the …, 2021 - openaccess.thecvf.com
Point clouds captured in real-world applications are often incomplete due to the limited
sensor resolution, single viewpoint, and occlusion. Therefore, recovering the complete point …

Pcn: Point completion network

W Yuan, T Khot, D Held, C Mertz… - … conference on 3D vision …, 2018 - ieeexplore.ieee.org
Shape completion, the problem of estimating the complete geometry of objects from partial
observations, lies at the core of many vision and robotics applications. In this work, we …

Dex-net 2.0: Deep learning to plan robust grasps with synthetic point clouds and analytic grasp metrics

J Mahler, J Liang, S Niyaz, M Laskey, R Doan… - ar** using generative residual convolutional neural network
S Kumra, S Joshi, F Sahin - 2020 IEEE/RSJ International …, 2020 - ieeexplore.ieee.org
In this paper, we present a modular robotic system to tackle the problem of generating and
performing antipodal robotic grasps for unknown objects from the n-channel image of the …