agentAR: Creating Augmented Reality Applications with Tool-Augmented LLM-based Autonomous Agents

agentAR: Creating Augmented Reality Applications with Tool-Augmented LLM-based Autonomous Agents

Creating Augmented Reality (AR) applications requires expertise in both design and implementation, posing significant barriers to entry for non-expert users. While existing methods reduce some of this burden, they often fall short in flexibility or usability for...
CARING-AI: Towards Authoring Context-aware Augmented Reality INstruction through Generative Artificial Intelligence

CARING-AI: Towards Authoring Context-aware Augmented Reality INstruction through Generative Artificial Intelligence

Context-aware AR instruction enables adaptive and in-situ learning experiences. However, hardware limitations and expertise requirements constrain the creation of such instructions. With recent developments in Generative Artificial Intelligence (Gen-AI), current...
Visualizing Causality in Mixed Reality for Manual Task Learning: A Study

Visualizing Causality in Mixed Reality for Manual Task Learning: A Study

Mixed Reality (MR) is gaining prominence in manual task skill learning due to its in-situ, embodied, and immersive experience. To teach manual tasks, current methodologies break the task into hierarchies (tasks into subtasks) and visualize not only the current...
avaTTAR: Table Tennis Stroke Training with On-body and Detached Visualization in Augmented Reality

avaTTAR: Table Tennis Stroke Training with On-body and Detached Visualization in Augmented Reality

Table tennis stroke training is a critical aspect of player development. We designed a new augmented reality (AR) system, avaTTAR, for table tennis stroke training. The system provides both “on-body” (first-person view) and “detached”...