Efficient and Accurate Candidate Generation for Grasp Pose Detection in SE(3)
Andreas ten Pas,Colin Keil,Robert Platt,Andreas ten Pas,Colin Keil,Robert Platt
Grasp detection of novel objects in unstructured environments is a key capability in robotic manipulation. For 2D grasp detection problems where grasps are assumed to lie in the plane, it is common to design a fully convolutional neural network that predicts grasps over an entire image in one step. However, this is not possible for grasp pose detection where grasp poses are assumed to exist in SE(...
