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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…
With the advancements in human-robot interaction (HRI), robots are now capable of operating in close proximity and engaging in physical interactions with humans (pHRI). Likewise, contact-based pHRI is becoming increasingly common as robots…
As robots become increasingly integrated into various industries, understanding how humans respond to robotic failures is critical. This study systematically examines trust dynamics and system design by analyzing human reactions to robot…
Assistive robot arms try to help their users perform everyday tasks. One way robots can provide this assistance is shared autonomy. Within shared autonomy, both the human and robot maintain control over the robot's motion: as the robot…
Robots learn as they interact with humans. Consider a human teleoperating an assistive robot arm: as the human guides and corrects the arm's motion, the robot gathers information about the human's desired task. But how does the human know…
Robots are becoming increasingly popular in a wide range of environments due to their exceptional work capacity, precision, efficiency, and scalability. This development has been further encouraged by advances in Artificial Intelligence,…
The number of robots deployed in our daily surroundings is ever-increasing. Even in the industrial set-up, the use of coworker robots is increasing rapidly. These cohabitant robots perform various tasks as instructed by co-located human…
Continual learning (CL) has emerged as an important avenue of research in recent years, at the intersection of Machine Learning (ML) and Human-Robot Interaction (HRI), to allow robots to continually learn in their environments over…
The field of human-human-robot interaction (HHRI) uses social robots to positively influence how humans interact with each other. This objective requires models of human understanding that consider multiple humans in an interaction as a…
Physical Human-Human Interaction (pHHI) involves the use of multiple sensory modalities. Studies of communication through spoken utterances and gestures are well established, but communication through force signals is not well understood.…
When robots interact with human partners, often these partners change their behavior in response to the robot. On the one hand this is challenging because the robot must learn to coordinate with a dynamic partner. But on the other hand --…
Wheelchair-mounted robotic arms (and other assistive robots) should help their users perform everyday tasks. One way robots can provide this assistance is shared autonomy. Within shared autonomy, both the human and robot maintain control…
To facilitate natural and intuitive interactions with diverse user groups in real-world settings, social robots must be capable of addressing the varying requirements and expectations of these groups while adapting their behavior based on…
People deeply care about how fairly they are treated by robots. The established paradigm for probing fairness in Human-Robot Interaction (HRI) involves measuring the perception of the fairness of a robot at the conclusion of an interaction.…
When a robot learns from human examples, most approaches assume that the human partner provides examples of optimal behavior. However, there are applications in which the robot learns from non-expert humans. We argue that the robot should…
Due to agile developments in the field of robotics and human-robot interaction, prospective robotic agents are intended to play the role of teammates and partner with humans to perform operations, rather than tools that are replacing humans…
Robot-Assisted Therapy (RAT) has successfully been used in Human Robot Interaction (HRI) research by including social robots in health-care interventions by virtue of their ability to engage human users in both social and emotional…
In Human-Robot Interaction (HRI) systems, a challenging task is sharing the representation of the operational environment, fusing symbolic knowledge and perceptions, between users and robots. With the existing HRI pipelines, users can teach…
Recent work in Human-Robot Interaction (HRI) has shown that robots can leverage implicit communicative signals from users to understand how they are being perceived during interactions. For example, these signals can be gaze patterns,…
This article presents a method for learning well-coordinated Human-Robot Interaction (HRI) from Human-Human Interactions (HHI). We devise a hybrid approach using Hidden Markov Models (HMMs) as the latent space priors for a Variational…