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

TL;DR

CARING-AI leverages generative AI to create context-aware AR instructions through natural environment navigation, enhancing adaptability and ease of authoring for diverse AR applications.

Contribution

The paper introduces CARING-AI, a novel AR system that uses Gen-AI to generate context-aware humanoid-avatar instructions based on environmental navigation.

Findings

User studies show high usability and ease of use.

System effectively generates context-adaptive AR instructions.

Demonstrated versatility across multiple application scenarios.

Abstract

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 research tries to tackle these constraints by deploying AI-generated content (AIGC) in AR applications. However, our preliminary study with six AR practitioners revealed that the current AIGC lacks contextual information to adapt to varying application scenarios and is therefore limited in authoring. To utilize the strong generative power of GenAI to ease the authoring of AR instruction while capturing the context, we developed CARING-AI, an AR system to author context-aware humanoid-avatar-based instructions with GenAI. By navigating in the environment, users naturally provide contextual information to generate humanoid-avatar animation as AR instructions that blend in the context spatially and temporally. We showcased three application scenarios of CARING-AI: Asynchronous Instructions, Remote Instructions, and Ad Hoc Instructions based on a design space of AIGC in AR Instructions. With two user studies (N=12), we assessed the system usability of CARING-AI and demonstrated the easiness and effectiveness of authoring with Gen-AI.