Navigation Pixie: Implementation and Empirical Study Toward On-demand Navigation Agents in Commercial Metaverse
Hikari Yanagawa, Yuichi Hiroi, Satomi Tokida, Yuji Hatada, Takefumi Hiraki

TL;DR
Navigation Pixie is an on-demand navigation agent that enhances user exploration in commercial metaverse platforms by integrating spatial metadata with language processing, validated through extensive cross-platform experiments.
Contribution
This work introduces Navigation Pixie, a novel, platform-independent navigation agent that combines spatial metadata with LLMs, and provides empirical evaluation in real-world metaverse settings.
Findings
Navigation Pixie increased dwell time and exploration in experiments.
User preferences varied between PC and VR environments.
The approach is effective across diverse commercial metaverse platforms.
Abstract
While commercial metaverse platforms offer diverse user-generated content, they lack effective navigation assistance that can dynamically adapt to users' interests and intentions. Although previous research has investigated on-demand agents in controlled environments, implementation in commercial settings with diverse world configurations and platform constraints remains challenging. We present Navigation Pixie, an on-demand navigation agent employing a loosely coupled architecture that integrates structured spatial metadata with LLM-based natural language processing while minimizing platform dependencies, which enables experiments on the extensive user base of commercial metaverse platforms. Our cross-platform experiments on commercial metaverse platform Cluster with 99 PC client and 94 VR-HMD participants demonstrated that Navigation Pixie significantly increased dwell time and free…
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