Cloud robotics has recently emerged as a collaborative technology between cloud
computing and service robotics enabled through progress in wireless networking, large …

Tactile sensing plays a pivotal role in achieving precise physical manipulation tasks and
extracting vital physical features. This comprehensive review paper presents an in-depth …

The nuclear industry has some of the most extreme environments in the world, with radiation
levels and extremely harsh conditions restraining human access to many facilities. One …

We propose a dual-module robotic system to tackle the problem of generating and
performing antipodal robotic grasps for unknown objects from the n-channel image of the …

In this study, we develop a framework for an intelligent and self-supervised industrial pick-
and-place operation for cluttered environments. Our target is to have the agent learn to …

Grip force control during robotic in-hand manipulation is usually modeled as a monolithic
task, where complex controllers consider the placement of all fingers and the contact states …

Bin-picking of small parcels and other textureless planar-faced objects is a common task at
warehouses. A general color image–based vision-guided robot picking system requires …

This paper focuses on develo** a robotic object gras** approach that possesses the
ability of self-learning, is suitable for small-volume large variety production, and has a high …

Objects in cluttered environments may have similar sizes and shapes, which remains a huge
challenge for robot gras** manipulation. The existing segmentation methods, such as …

Compared to traditional data-driven learning methods, recently developed deep
reinforcement learning (DRL) approaches can be employed to train robot agents to obtain …