In order to complete many complex operations and attain more general-purpose utility,
robotic grasp is a necessary skill to master. As the most common essential action of robots in …

Robotic dexterous gras** is the first step to enable human-like dexterous object
manipulation and thus a crucial robotic technology. However, dexterous gras** is much …

As there come to be more applications of intelligent robots, their task object is becoming
more varied. However, it is still a challenge for a robot to handle unfamiliar objects. We …

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 …

Gras** and assembly are essential tasks in high-precision robotic manipulation for
industrial manufacturing as well as for home service applications. Many efforts have been …

Deep learning-based robotic gras** has made significant progress thanks to algorithmic
improvements and increased data availability. However, state-of-the-art models are often …

Existing grasp synthesis methods are either analytical or data-driven. The former one is
oftentimes limited to specific application scope. The latter one depends heavily on …

Gras** and manipulating objects is an important human skill. Since most objects are
designed to be manipulated by human hands, anthropomorphic hands can enable richer …

In recent years, many dexterous robotic hands have been designed to assist or replace
human hands in executing various tasks. But how to teach them to perform dexterous …

Dexterous gras** aims to produce diverse gras** postures with a high gras**
success rate. Regression-based methods that directly predict gras** parameters given the …