Related papers: Learning Visualization Policies of Augmented Reali…
Understanding human intentions is critical for safe and effective human-robot collaboration. While state of the art methods for human goal prediction utilize learned models to account for the uncertainty of human motion data, that data is…
Effective human-robot collaboration (HRC) requires extensive communication among the human and robot teammates, because their actions can potentially produce conflicts, synergies, or both. We develop a novel augmented reality (AR) interface…
End-to-end robot policies achieve high performance through neural networks trained via reinforcement learning (RL). Yet, their black box nature and abstract reasoning pose challenges for human-robot interaction (HRI), because humans may…
Human-robot collaboration (HRC) has become increasingly relevant in industrial, household, and commercial settings. However, the effectiveness of such collaborations is highly dependent on the human and robots' situational awareness of the…
Augmented Reality (AR) provides a safe and low-cost option for hazardous safety training that allows for the visualization of aspects that may be invisible, such as radiation. Effectively visually communicating such threats in the…
Autonomous warehouses with mobile, rack-carrying robots are starting to become commonplace, with systems such as Amazon's Kiva and Swisslog's CarryPick already implemented in functional warehouses. Such warehouses however still require…
The field of visual representation learning has seen explosive growth in the past years, but its benefits in robotics have been surprisingly limited so far. Prior work uses generic visual representations as a basis to learn (task-specific)…
One huge advantage of Augmented Reality (AR) is its numerous possibilities of displaying information in the physical world, especially when applying Situated Analytics (SitA). AR devices and their respective interaction techniques allow for…
Reinforcement learning (RL) algorithms can find an optimal policy for a single agent to accomplish a particular task. However, many real-world problems require multiple agents to collaborate in order to achieve a common goal. For example, a…
The current spread of social and assistive robotics applications is increasingly highlighting the need for robots that can be easily taught and interacted with, even by users with no technical background. Still, it is often difficult to…
Today's robots attempt to learn new tasks by imitating human examples. These robots watch the human complete the task, and then try to match the actions taken by the human expert. However, this standard approach to visual imitation learning…
In this work, we investigate Active Vision Reinforcement Learning (ActiveVision-RL), where an embodied agent simultaneously learns action policy for the task while also controlling its visual observations in partially observable…
Interactive adaptive systems powered by Reinforcement Learning (RL) have many potential applications, such as intelligent tutoring systems. In such systems there is typically an external human system designer that is creating, monitoring…
Humans are highly skilled in communicating their intent for when and where a handover would occur. However, even the state-of-the-art robotic implementations for handovers typically lack of such communication skills. This study investigates…
Interactive reinforcement learning, where humans actively assist during an agent's learning process, has the promise to alleviate the sample complexity challenges of practical algorithms. However, the inner workings and state of the robot…
The concept of augmented reality (AR) assistants has captured the human imagination for decades, becoming a staple of modern science fiction. To pursue this goal, it is necessary to develop artificial intelligence (AI)-based methods that…
Safety is a fundamental requirement in any human-robot collaboration scenario. To ensure the safety of users for such scenarios, we propose a novel Virtual Barrier system facilitated by an augmented reality interface. Our system provides…
When establishing a visual connection between a virtual reality user and an augmented reality user, it is important to consider whether the augmented reality user faces a surplus of information. Augmented reality, compared to virtual…
When humans work together to complete a joint task, each person builds an internal model of the situation and how it will evolve. Efficient collaboration is dependent on how these individual models overlap to form a shared mental model…
Understanding how helpful a visualization is from experimental results is difficult because the observed performance is confounded with aspects of the study design, such as how useful the information that is visualized is for the task. We…