SCIUTTI A.

Since infancy we explore novel objects to infer their shape. However, how exploration strategies are planned to combine different sensory inputs is still an open question. In this work we focus on the development of visuo-haptic exploration strategies, by analyzing how school-aged children explore iCube, a sensorized cube measuring its...

In this paper, we investigate whether information related to touches and rotations impressed to an object can be effectively used to classify the emotion of the agent manipulating it. We specifically focus on sequences of basic actions (e.g., grasping, rotating), which are constituents of daily interactions. We use the iCube, a 5 cm cube...

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In the industry of the future, so as in healthcare and at home, robots will be a familiar presence. Since they will be working closely with human operators not always properly trained for human-machine interaction tasks, robots will need the ability of automatically adapting to changes in the task to be performed or to cope with variations in...

Robots such as information security and overtrust in them are gaining increasing relevance. This research aims at giving an insight into how trust toward robots could be exploited for the purpose of social engineering. Drawing on Mitnick's model, a well-known social engineering framework, an interactive scenario with the humanoid robot iCub was...

This paper proposes a method based on visual motion primitives to address the problem of action understanding. The approach builds in an unsupervised way a dictionary of kinematic primitives from a set of sub-movements obtained by segmenting the velocity profile of an action on the basis of local minima derived directly from the optical flow....

A social robot that's aware of our needs and continuously adapts its behaviour to them has the potential of creating a complex, personalized, human-like interaction of the kind we are used to have with our peers in our everyday lives. However adaptability, being a result of a process of learning and making errors, brings with itself also...

A social robot that is aware of our needs and continuously adapts its behaviour to them has the potential of creating a complex, personalized, human-like interaction of the kind we are used to have with our peers in our everyday lives. We are interested in exploring how would an adaptive architecture function and personalize to different users...

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We investigate the recognition of the affective states of a person performing an action with an object, by processing the object-sensed data. We focus on sequences of basic actions such as grasping and rotating, which are constituents of daily-life interactions. iCube, a 5 cm cube, was used to collect tactile and kinematics data that consist of...

Humans are excellent at perceiving different features of the actions performed by others. For instance, by viewing someone else manipulating an unknown object, one can infer its weight–an intrinsic feature otherwise not directly accessible through vision. How such perceptual skill develops during childhood remains unclear. To confront this gap,...

Human motion understanding has been studied for decades but yet it remains a challenging research field which attracts the interest from different disciplines. This book wants to provide a comprehensive view on this topic, closing the loop between perception and action, starting from humans' action perception skills and then moving to...

MoCA is a bi-modal dataset in which we collect Motion Capture data and video sequences acquired from multiple views, including an ego-like viewpoint, of upper body actions in a cooking scenario. It has been collected with the specific purpose of investigating view-invariant action properties in both biological and artificial systems. Besides...

Social interactions entail often complex and dynamic situations that follow non-explicit, unwritten rules. Comprehending those signals and knowing how to respond becomes the key to the success of any social communication. Thus, in order to integrate a robot into a social context it should be capable of (at least) understanding others' emotional...

The high request for autonomous human-robot interaction (HRI), combined with the potential of machine learning (ML) techniques, allow us to deploy ML mechanisms in robot control. However, the use of ML can make robots' behavior unclear to the observer during the learning phase. Recently, transparency in HRI has been investigated to make such...

When faced with a novel object, we explore it to understand its shape. This way we combine information coming from different senses, as touch, proprioception and vision, together with the motor information embedded in our motor execution plan. The exploration process provides a structure and constrains this rich flow of inputs, supporting the...

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Lie detection is a necessary skill for a variety of social professions, including teachers, reporters, therapists, and law enforcement officers. Autonomous system and robots should acquire such skill to support professionals in numerous working contexts. Inspired by literature on human-human interaction, this work investigates whether the...

Robots destined to tasks like teaching or caregiving have to build a long-lasting social rapport with their human partners. This requires, from the robot side, to be capable of assessing whether the partner is trustworthy. To this aim a robot should be able to assess whether someone is lying or not, while preserving the pleasantness of the...

Detecting lies in a real-world scenario is an important skill for a humanoid robot that aims to act as a teacher, a therapist, or a caregiver. In these contexts, it is essential to detect lies while preserving the pleasantness of the social interaction and the informality of the relation. This study investigates whether pupil dilation related...