Instance-Enriched Semantic Maps for Visual Language Navigation
Visual Language Navigation (VLN) aims to enable an embodied agent to navigate complex environments by following natural language instructions. Recent approaches build semantic spatial maps and leverage Large Language Models (LLMs) for reasoning and decision making. Despite these advances, existing systems lack instance-level object detail and robustness to diverse user queries, limiting reliable navigation in complex indoor environments. To address these limitations, we propose Instance-Enriched Semantic Maps, a unified framework with three key contributions: (1) Instance-level two-and-a-half-dimensional (2.5D) rich information mapping that constructs maps from color and depth observation...
| Authors | Jiho Hong, Eunae Kang, Sanghyun Kim et al. |
|---|---|
| Primary category | cs.RO |
| Published | 14 July 2026 |
| Last updated at source | 17 July 2026 |
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