ACM Transactions on Human-Robot Interaction

Social robots in our daily surroundings, like personal guides, waiter robots, home helpers, assistive robots, telepresence/teleoperation robots etc., are increasing day by day. Their usability and acceptability largely depend on their explicit and ...

We developed a security guard robot that is specifically designed to manage queues of people and conducted a field trial at an actual public event to assess its effectiveness. However, the acceptance of robot instructions or admonishments poses challenges ...

The deployment of autonomous delivery robots in urban environments presents unique challenges in navigating complex traffic conditions and interacting with diverse road and sidewalk users. Effective communication between robots and road and sidewalk users ...

In this paper, we report on methodological insights gained from a workshop in which we collaborated with theater professionals to enact situated encounters between humans and robots on a mixed reality stage combining VR with real-life interaction. We ...

In Human-Robot Interaction, researchers typically utilize in-person studies to collect subjective perceptions of a robot. In addition, videos of interactions and interactive simulations (where participants control an avatar that interacts with a robot in ...

Trust is crucial for technological acceptance, continued usage, and teamwork. However, human-robot trust, and human-machine trust more generally, suffer from terminological disagreement and construct proliferation. By comparing, mapping, and analyzing ...

Mobile telepresence robots can help reduce loneliness by facilitating people to visit each other and have more social presence than visiting via video or audio calls. However, using new technology can be challenging for many older adults. In this paper, ...

For humans to effectively work with robots, they must be able to predict the actions and behaviors of their robot teammates rather than merely react to them. While there are existing techniques enabling robots to adapt to human behavior, there is a ...

Despite the existence of robots that can lift heavy loads, robots that can help people move heavy objects are not readily available. This paper makes progress towards effective human-robot co-manipulation by studying 30 human-human dyads that ...

While there is evidence that human-like characteristics in robots could benefit child-robot interaction in many ways, open questions remain about the appropriate degree of human likeness that should be implemented in robots to avoid adverse effects on ...

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 long-term interactions ...

When robots have multiple tasks to perform, they must determine the order in which to complete them. Interleaving tasks is efficient for the robot trying to finish its to-do list, but it may be less satisfying for a human whose request was delayed in ...

Human-robot interaction (HRI) in human social environments (HSEs) poses unique challenges for robot perception systems, which must combine asynchronous, heterogeneous data streams in real-time. Multimodal perception systems are well-suited for HRI in HSEs,...

In human-robot interaction studies, trust is often defined as a process whereby a trustor makes themselves vulnerable to a trustee. The role of vulnerability however is often overlooked in this process but could play an important role in the gaining and ...

Intention prediction has become a relevant field of research in Human-Machine and Human-Robot Interaction. Indeed, any artificial system (co)-operating with and along humans, designed to assist and coordinate its actions with a human partner, would ...

The automation of the car charging process is motivated by the rapid development of technologies for self-driving cars and the increasing importance of ecological transportation units. Automation of this process requires the implementation of Computer ...

Teleoperation systems find many applications from earlier search-and-rescue to more recent daily tasks. It is widely acknowledged that using external sensors can decouple the view of the remote scene from the motion of the robot arm during manipulation, ...

During the last 15 years, an increasing amount of works have investigated proactive robotic behavior in relation to Human-Robot Interaction (HRI). The works engage with a variety of research topics and technical challenges. In this paper a review of the ...

When individuals are paralyzed from injury or damage to the brain, upper body movement and function can be compromised. While the use of body motions to interface with machines has shown to be an effective noninvasive strategy to provide movement ...

In teleoperation of redundant robotic manipulators, translating an operator’s end effector motion command to joint space can be a tool for maintaining feasible and precise robot motion. Through optimizing redundancy resolution, the control system can ...

Remote robot manipulation with human control enables applications where safety and environmental constraints are adverse to humans (e.g. underwater, space robotics and disaster response) or the complexity of the task demands human-level cognition and ...

Robots are moving from working in isolation to working with humans as a part of human-robot teams. In such situations, they are expected to work with multiple humans and need to understand and predict the team members’ actions. To address this challenge, ...

In this work, we present a method for personalizing human-robot interaction by using emotive facial expressions to generate affective robot movements. Movement is an important medium for robots to communicate affective states, but the expertise and time ...

Humans can leverage physical interaction to teach robot arms. This physical interaction takes multiple forms depending on the task, the user, and what the robot has learned so far. State-of-the-art approaches focus on learning from a single modality, or ...

Natural language instructions are effective at tasking autonomous robots and for teaching them new knowledge quickly. Yet, human instructors are not perfect and are likely to make mistakes at times, and will correct themselves when they notice errors in ...

Collaborative human-robot task execution approaches require mutual adaptation, allowing both the human and robot partners to take active roles in action selection and role assignment to achieve a single shared goal. Prior works have utilized a leader-...

The creation of information transparency solutions to enable humans to understand robot perception is a challenging requirement for autonomous and artificially intelligent robots to impact a multitude of domains. By taking advantage of comprehensive and ...

This paper proposes a novel stochastic-skill-level-based shared control framework to assist human novices to emulate human experts in complex dynamic control tasks. The proposed framework aims to infer stochastic-skill-levels (SSLs) of the human novices ...