相关论文: Modeling User Empathy Elicited by a Robot Storytel…

Industrial robots become increasingly prevalent, resulting in a growing need for intuitive, comforting human-robot collaboration. We present a user-aware robotic system that adapts to operator behavior in real time while non-intrusively…

As collaborative robots enter industrial shop floors, logistics, and manufacturing, rapid and flexible evaluation of human-machine interaction has become more important. The availability of consumer headsets for virtual and augmented…

In an effort to improve how robots function in social contexts, this paper investigates if a robot that actively shares a reaction to an event with a human alters how the human perceives the robot's affective impact. To verify this, we…

Prior efforts to create an autonomous computer system capable of predicting what a human being is thinking or feeling from facial expression data have been largely based on outdated, inaccurate models of how emotions work that rely on many…

Teleoperated robotic characters can perform expressive interactions with humans, relying on the operators' experience and social intuition. In this work, we propose to create autonomous interactive robots, by training a model to imitate…

Safe human-robot interactions require robots to be able to learn how to behave appropriately in \sout{humans' world} \rev{spaces populated by people} and thus to cope with the challenges posed by our dynamic and unstructured environment,…

To better interact with users, a social robot should understand the users' behavior, infer the intention, and respond appropriately. Machine learning is one way of implementing robot intelligence. It provides the ability to automatically…

Empathetic response from the therapist is key to the success of clinical psychotherapy, especially motivational interviewing. Previous work on computational modelling of empathy in motivational interviewing has focused on offline,…

Empathy involves understanding other people's situation, perspective, and feelings. In clinical interactions, it helps clinicians establish rapport with a patient and support patient-centered care and decision making. Understanding…

Zoomorphic robots have the potential to offer companionship and well-being as accessible, low-maintenance alternatives to pet ownership. Many such robots, however, feature limited emotional expression, restricting their potential for rich…

When deploying interactive agents like (social) robots in public spaces they need to be able to interact with a diverse audience, with members each having individual diversity characteristics and prior experiences with interactive systems.…

Learning therapeutic counseling involves significant role-play experience with mock patients, with current manual training methods providing only intermittent granular feedback. We seek to accelerate and optimize counselor training by…

Effective communication is essential in collaborative tasks, so AI-equipped robots working alongside humans need to be able to explain their behaviour in order to cooperate effectively and earn trust. We analyse and classify communications…

Many children experience challenges in emotional regulation and social interaction, which can limit their participation in everyday activities and therapeutic programs. For socially assistive robots to be effective in this context, it is…

Robotic ultrasound systems can enhance medical diagnostics, but patient acceptance is a challenge. We propose a system combining an AI-powered conversational virtual agent with three mixed reality visualizations to improve trust and…

Empathetic Conversational Systems (ECS) are built to respond empathetically to the user's emotions and sentiments, regardless of the application domain. Current ECS studies evaluation approaches are restricted to offline evaluation…

With the advent of generative AI and large language models, embodied conversational agents are becoming synonymous with online interactions. These agents possess vast amounts of knowledge but suffer from exhibiting limited emotional…

Learning collaborative behaviors is essential for multi-agent systems. Traditionally, multi-agent reinforcement learning solves this implicitly through a joint reward and centralized observations, assuming collaborative behavior will…

One of the challenges of telepresence robotics is to provide ubiquitous social-interpersonalimmersion. In order to achieve this, there is a need to understand and model the factors that wouldallow the users to control the transmission of…

Reinforcement learning techniques successfully generate convincing agent behaviors, but it is still difficult to tailor the behavior to align with a user's specific preferences. What is missing is a communication method for the system to…