Navigation Pixie: Implementation and Empirical Study Toward On-demand Navigation Agents in Commercial Metaverse
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866916882246795264 |
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| author | Yanagawa, Hikari Hiroi, Yuichi Tokida, Satomi Hatada, Yuji Hiraki, Takefumi |
| author_facet | Yanagawa, Hikari Hiroi, Yuichi Tokida, Satomi Hatada, Yuji Hiraki, Takefumi |
| contents | 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 exploration compared to fixed-route and no-agent conditions across both platforms. Subjective evaluations revealed consistent on-demand preferences in PC environments versus context-dependent social perception advantages in VR-HMD. This research contributes to advancing VR interaction design through conversational spatial navigation agents, establishes cross-platform evaluation methodologies revealing environment-dependent effectiveness, and demonstrates empirical experimentation frameworks for commercial metaverse platforms. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2508_03216 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Navigation Pixie: Implementation and Empirical Study Toward On-demand Navigation Agents in Commercial Metaverse Yanagawa, Hikari Hiroi, Yuichi Tokida, Satomi Hatada, Yuji Hiraki, Takefumi Human-Computer Interaction Artificial Intelligence 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 exploration compared to fixed-route and no-agent conditions across both platforms. Subjective evaluations revealed consistent on-demand preferences in PC environments versus context-dependent social perception advantages in VR-HMD. This research contributes to advancing VR interaction design through conversational spatial navigation agents, establishes cross-platform evaluation methodologies revealing environment-dependent effectiveness, and demonstrates empirical experimentation frameworks for commercial metaverse platforms. |
| title | Navigation Pixie: Implementation and Empirical Study Toward On-demand Navigation Agents in Commercial Metaverse |
| topic | Human-Computer Interaction Artificial Intelligence |
| url | https://arxiv.org/abs/2508.03216 |