Recent work in 6D object pose estimation holds significant promise for advancing robotics, augmented reality (AR), virtual reality (VR), as well as autonomous navigation. The research, published in ...

Abstract: Unordered grasping in industrial robotic manipulation requires precise six-degree-of-freedom (6D) pose estimation. However, existing methods often struggle with unknown objects and require ...

Abstract: Deep Learning (DL) has become essential in various robotics applications due to excelling at processing raw sensory data to extract task specific information from semantic objects. For ...

Robots are good at making identical repetitive movements, such as a simple task on an assembly line. (Pick up a cup. Turn it over. Put it down.) But they lack the ability to perceive objects as they ...

Researchers have developed a novel 6D pose dataset designed to improve robotic grasping accuracy and adaptability in industrial settings. The dataset, which integrates RGB and depth images, ...