We review the work on data-driven grasp synthesis and the methodologies for sampling and
ranking candidate grasps. We divide the approaches into three groups based on whether …

We consider the problem of detecting robotic grasps in an RGB-D view of a scene
containing objects. In this work, we apply a deep learning approach to solve this problem …

We present an algorithm for fast global registration of partially overlap** 3D surfaces. The
algorithm operates on candidate matches that cover the surfaces. A single objective is …

3D object recognition in cluttered scenes is a rapidly growing research area. Based on the
used types of features, 3D object recognition methods can broadly be divided into two …

For robots to navigate and interact more richly with the world around them, they will likely
require a deeper understanding of the world in which they operate. In robotics and related …

Aiming at accelerating the creation of new techniques on dexterous robotic manipulations,
this paper surveyed the recent results on object recognition, soft robotic hands, and …

For collaborative robots to become useful, end users who are not robotics experts must be
able to instruct them to perform a variety of tasks. With this goal in mind, we developed a …

Global registration is a fundamental task that estimates the relative pose between two
viewpoints of 3D point clouds. However, there are two issues that degrade the performance …

Abstract We introduce the MVTec Industrial 3D Object Detection Dataset (MVTec ITODD), a
public dataset for 3D object detection and pose estimation with a strong focus on ob-jects …

This article presents an efficient and robust estimator called compatibility-guided sampling
consensus (CG-SAC) to achieve accurate 3-D point cloud registration. For correspondence …