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To interact with humans in collaborative environments, machines need to be able to predict (i.e., anticipate) future events, and execute actions in a timely manner. However, the observation of the human limb movements may not be sufficient…

Robotics · Computer Science 2020-06-19 Clebeson Canuto , Plinio Moreno , Jorge Samatelo , Raquel Vassallo , José Santos-Victor

Human interaction involves very sophisticated non-verbal communication skills like understanding the goals and actions of others and coordinating our own actions accordingly. Neuroscience refers to this mechanism as motor resonance, in the…

Robotics · Computer Science 2019-05-13 Nuno Ferreira Duarte , Mirko Raković , José Santos-Victor

Humans are constantly influenced by others' behavior and opinions. Of importance, social influence among humans is shaped by reciprocity: we follow more the advice of someone who has been taking into consideration our opinions. In the…

Robotics · Computer Science 2022-06-17 Joshua Zonca , Anna Folso , Alessandra Sciutti

While interacting with another person, our reactions and behavior are much affected by the emotional changes within the temporal context of the interaction. Our intrinsic affective appraisal comprising perception, self-assessment, and the…

Human-Computer Interaction · Computer Science 2019-08-05 Pablo Barros , Stefan Wermter , Alessandra Sciutti

Recent research on human robot interaction explored whether people's tendency to conform to others extends to artificial agents (Hertz & Wiese, 2016). However, little is known about to what extent perception of a robot as having a mind…

Robotics · Computer Science 2018-11-05 Deniz Lefkeli , Baris Akgun , Sahibzada Omar , Aansa Malik , Zeynep Gurhan Canli , Terry Eskenazi

The development of assistive robots for social collaboration raises critical questions about responsible and inclusive design, especially when interacting with individuals from protected groups such as those with disabilities or advanced…

Robotics · Computer Science 2025-07-23 Sabrina Livanec , Laura Londoño , Michael Gorki , Adrian Röfer , Abhinav Valada , Andrea Kiesel

We report on an extensive study of the benefits and limitations of current deep learning approaches to object recognition in robot vision scenarios, introducing a novel dataset used for our investigation. To avoid the biases in currently…

Robotics · Computer Science 2021-08-25 Giulia Pasquale , Carlo Ciliberto , Francesca Odone , Lorenzo Rosasco , Lorenzo Natale

Mind perception in robots has been an understudied construct in human-robot interaction (HRI) compared to similar concepts such as anthropomorphism and the intentional stance. In a series of three experiments, we identify two factors that…

Robotics · Computer Science 2020-04-17 Sebastian Wallkotter , Rebecca Stower , Arvid Kappas , Ginevra Castellano

Purpose of Review: The field of humanoid robotics, perception plays a fundamental role in enabling robots to interact seamlessly with humans and their surroundings, leading to improved safety, efficiency, and user experience. This…

Robotics · Computer Science 2023-09-28 Arindam Roychoudhury , Shahram Khorshidi , Subham Agrawal , Maren Bennewitz

The study of human-robot interaction is fundamental to the design and use of robotics in real-world applications. Robots will need to predict and adapt to the actions of human collaborators in order to achieve good performance and improve…

Gaze is a crucial social cue in any interacting scenario and drives many mechanisms of social cognition (joint and shared attention, predicting human intention, coordination tasks). Gaze direction is an indication of social and emotional…

Robotics · Computer Science 2024-10-28 Maria Lombardi , Elisa Maiettini , Agnieszka Wykowska , Lorenzo Natale

One of the open challenges in designing robots that operate successfully in the unpredictable human environment is how to make them able to predict what actions they can perform on objects, and what their effects will be, i.e., the ability…

Recent studies suggest that cooperative decision-making in one-shot interactions is a history-dependent dynamic process: promoting intuition versus deliberation has typically a positive effect on cooperation (dynamism) among people living…

Populations and Evolution · Quantitative Biology 2015-06-10 Valerio Capraro , Giorgia Cococcioni

Understanding human perceptions of robot performance is crucial for designing socially intelligent robots that can adapt to human expectations. Current approaches often rely on surveys, which can disrupt ongoing human-robot interactions. As…

Skilled motor behavior is critical in many human daily life activities and professions. The design of robots that can effectively teach motor skills is an important challenge in the robotics field. In particular, it is important to…

Robotics · Computer Science 2020-11-02 Giulia Belgiovine , Francesco Rea , Jacopo Zenzeri , Alessandra Sciutti

Memory is fundamental to social interaction, enabling humans to recall meaningful past experiences and adapt their behavior accordingly based on the context. However, most current social robots and embodied agents rely on non-selective,…

Artificial Intelligence · Computer Science 2026-04-15 Hangyeol Kang , Slava Voloshynovskiy , Nadia Magnenat Thalmann

Humans have an extraordinary ability to communicate and read the properties of objects by simply watching them being carried by someone else. This level of communicative skills and interpretation, available to humans, is essential for…

Ensuring that robot navigation is safe and socially acceptable is crucial for comfortable human-robot interaction in shared environments. However, existing validation methods often rely on a bird's-eye (allocentric) perspective, which fails…

Robotics · Computer Science 2026-03-31 Subham Agrawal , Aftab Akthar , Nils Dengler , Maren Bennewitz

Affective touch in human-robot interaction is shaped not only by emotional intent, but also by robot embodiment, including touch location, physical constraints, and perceived agency or social role. Existing HRI studies typically focus on…

A key challenge in reward learning from human input is that desired agent behavior often changes based on context. For example, a robot must adapt to avoid a stove once it becomes hot. We observe that while high-level preferences (e.g.,…

Robotics · Computer Science 2026-01-14 Alexandra Forsey-Smerek , Julie Shah , Andreea Bobu