Related papers: Towards Transparency of TD-RL Robotic Systems with…
The adoption of Reinforcement Learning (RL) in several human-centred applications provides robots with autonomous decision-making capabilities and adaptability based on the observations of the operating environment. In such scenarios,…
Human emotions are expressed through multiple modalities, including verbal and non-verbal information. Moreover, the affective states of human users can be the indicator for the level of engagement and successful interaction, suitable for…
To facilitate effective human-robot interaction (HRI), trust-aware HRI has been proposed, wherein the robotic agent explicitly considers the human's trust during its planning and decision making. The success of trust-aware HRI depends on…
Human acceptance of social robots is greatly effected by empathy and perceived understanding. This necessitates accurate and flexible responses to various input data from the user. While systems such as this can become increasingly complex…
Transparency is an important aspect of human-robot interaction (HRI), as it can improve system trust and usability leading to improved communication and performance. However, most transparency models focus only on the amount of information…
In recent years, an increased effort has been invested to improve the capabilities of robots. Nevertheless, human-robot interaction remains a complex field of application where errors occur frequently. The reasons for these errors can…
Human-robot collaboration (HRC) can benefit from robots' abilities to interpret human emotional states. However, current emotion recognition (ER) models in HRC often fall short, particularly due to their reliance on acted datasets and…
Being able to recognize emotions in human users is considered a highly desirable trait in Human-Robot Interaction (HRI) scenarios. However, most contemporary approaches rarely attempt to apply recognized emotional features in an active…
Robots can support humans in tedious tasks, as well as provide social support. However, the decision-making and behavior of robots is not always clear to the human interaction partner. In this work, we discuss the opportunity of using…
In human-robot interaction (HRI), we study how humans interact with robots, but also the effects of robot behavior on human perception and well-being. Especially, the influence on humans by tandem robots with one human controlled and one…
Service and assistive robots are increasingly being deployed in dynamic social environments; however, ensuring transparent and explainable interactions remains a significant challenge. This paper presents a multimodal explainability module…
Recently, collaborative robots have begun to train humans to achieve complex tasks, and the mutual information exchange between them can lead to successful robot-human collaborations. In this paper we demonstrate the application and…
As robots get more integrated into human environments, fostering trustworthiness in embodied robotic agents becomes paramount for an effective and safe human-robot interaction (HRI). To achieve that, HRI applications must promote human…
Transparency is a key factor in improving the performance of human-robot interaction. A transparent interface allows humans to be aware of the state of a robot and to assess the progress of the tasks at hand. When multi-robot systems are…
Tactile information is important for robust performance in robotic tasks that involve physical interaction, such as object manipulation. However, with more data included in the reasoning and control process, modeling behavior becomes…
HRI research increasingly demands robots that go beyond task execution to respond meaningfully to user emotions. This is especially needed when supporting students with learning difficulties in game-based learning scenarios. Here, the…
This article provides the first survey of computational models of emotion in reinforcement learning (RL) agents. The survey focuses on agent/robot emotions, and mostly ignores human user emotions. Emotions are recognized as functional in…
As the autonomy and capabilities of robotic systems increase, they are expected to play the role of teammates rather than tools and interact with human collaborators in a more realistic manner, creating a more human-like relationship. Given…
The overarching goal of this work is to efficiently enable end-users to correctly anticipate a robot's behavior in novel situations. Since a robot's behavior is often a direct result of its underlying objective function, our insight is that…
Expressive behaviors in robots are critical for effectively conveying their emotional states during interactions with humans. In this work, we present a framework that autonomously generates realistic and diverse robotic emotional…