We propose a dataset to study the influence of object-specific characteristics on human pick-
and-place movements and compare the quality of the motion kinematics extracted by …

In the research area of human-robot interactions, the automatic estimation of the mass of a
container manipulated by a person leveraging only visual information is a challenging task …

Estimating the 6D pose and size of household containers is challenging due to large intra-
class variations in the object properties, such as shape, size, appearance, and transparency …

Visual affordance segmentation identifies image regions of an object an agent can interact
with. Existing methods re-use and adapt learning-based architectures for semantic …

Human-robot collaboration requires the contactless estimation of the physical properties of
containers manipulated by a person, for example while pouring content in a cup or moving a …

Liquids and granular media are pervasive throughout human environments, yet remain
particularly challenging for robots to sense and manipulate precisely. In this work, we …

Pouring snacks and moving containers with beverages are challenging for a service robot.
To obtain accurate content properties for planning robotic motion, tactile sensing can …

The prediction of affordances ie, the potential actions an agent can perform on objects in the
scene, is fundamental for human-robot collaboration and wearable robotics scenarios in …

As human beings, having social connections plays a crucial role in our lives, and our
interactions are based on communication. Much of the exchange of information occurs in a …

We need the help of robots in unstructured environments such as our living spaces or
hazardous areas. These environments contain numerous tasks and objects to deal with …