This paper presents a comprehensive survey on vision-based robotic grasping. We
conclude three key tasks during vision-based robotic grasping, which are object localization …

One critical challenge in 6D object pose estimation from a single RGBD image is efficient
integration of two different modalities, ie, color and depth. In this work, we tackle this problem …

As RGB-D sensors become more affordable, using RGB-D images to obtain high-accuracy
6D pose estimation results becomes a better option. State-of-the-art approaches typically …

We present a large-scale stereo RGB image object pose estimation dataset named the
StereOBJ-1M dataset. The dataset is designed to address challenging cases such as object …

Current state-of-the-art pose estimation methods are almost launched on segmented RGB-D
images. However, these methods may not apply to more general industrial parts due to a …

Abstract 6D object pose estimation plays an important role in various applications such as
robot manipulation and virtual reality. In this paper, we introduce a graph convolution neural …

The 6-D pose estimation is a crucial task in vision-based measurement for robotic
manipulation. It becomes a challenging task because of the variety of lighting conditions …

In this work we introduce a novel method for calculating the 6DoF pose of an object using a
single RGB-D image. Unlike existing methods that either directly predict objects' poses or …

The socio-economic need for service robots has become more evident during the ongoing
pandemic. To boost their deployment, robots need to improve their manipulation …

Recently, applying the utilization of RGB-D data for robot perception tasks has garnered
significant attention in domains like robotics and autonomous driving. However, a prominent …