arXiv (All)
open access
UrbanVLA: A Vision-Language-Action Model for Urban Micromobility
Urban micromobility applications, such as delivery robots, demand reliable navigation across large-scale urban environments while following long-horizon route instructions. This task is particularly challenging due to the dynamic and unstructured nature of real-world city areas, yet most existing na
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- RiverVLN: Phase-Grounded Temporal Vision--Language Navigation for Unmanned Surface Vehicles#1049164
- LM-X: Explainable Vision--Language--Action Modeling via Progress, Event, and Uncertainty Prediction#987808
- OREN-X: Octree Residual Network for Real-Time Multi-Modal Mapping#1077086
- EdgeVLN: Runtime-Aware Deployment Ready Quantized Vision Language Navigation Model#1130226
- G2-Nav: Grounded and Guarded Vision-Language Costmaps for Robot Social Navigation#1156431
Record · ID 1155070
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive