Tactile sensing is a key sensor modality for robots interacting with their surroundings. These
sensors provide a rich and diverse set of data signals that contain detailed information …

Touch sensing can help robots understand their surrounding environment, and in particular
the objects they interact with. To this end, roboticists have, in the last few decades …

Advances in deep learning over the last decade have led to a flurry of research in the
application of deep artificial neural networks to robotic systems, with at least 30 papers …

The twenty-first century is undergoing a fundamental transition in the way things are created
and services are provided. The digitalization of services has resulted in a compelling, major …

The ever-increasing complexity of robot applications induces the need for methods to
approach problems with no (viable) analytical solution. Deep learning (DL) provides a set of …

Recent advancements in computer vision have enabled wide-ranging applications in every
field of life. One such application area is fresh produce classification, but the classification of …

The camera provides rich visual information regarding objects and becomes one of the most
mainstream sensors in the automation community. However, it is often difficult to be …

The Advancements in tactile sensors and machine learning techniques open new
opportunities for achieving intelligent gras** in robotics. Traditional robot is limited in its …

Novel high-resolution pressure-sensor arrays allow treating pressure readings as standard
images. Computer vision algorithms and methods such as convolutional neural networks …

Robotic grippers can be equipped with tactile sensing systems to extract information from a
manipulated object. The real-time classification of the physical properties of a grasped …