Antipodal Robotic Grasping using Generative Residual Convolutional Neural Network
Sulabh Kumra,Shirin Joshi,Ferat Sahin,Sulabh Kumra,Shirin Joshi,Ferat Sahin
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 scene. We propose a novel Generative Residual Convolutional Neural Network (GR-ConvNet) model that can generate robust antipodal grasps from n-channel input at real-time speeds (~20ms). We evaluate the proposed model arch...
