arXiv (All)
open access
SERF: Spatiotemporal Environment and Robot Feature Map for Long-Horizon Mobile Manipulation
Long-horizon robot mobile manipulation requires continual reasoning about localization, environment changes, and task progress, all of which are challenging to infer from image observations alone. In this paper, we show that conditioning a mobile manipulation policy on a spatiotemporal feature map i
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
- FRAM: Trajectory-Guided Visual Feature Selection for Compact Language-Conditioned Robot Manipulation#1105524
- PACE: Stage-Consistent Long-Horizon Robot Manipulation via Progress-Aligned Context for Execution#1217652
- Articulated 3D Scene Graphs for Open-World Mobile Manipulation#1328388
- MAVP: Map-Aware Visuomotor Policies for Mobile Manipulation#1062274
- MAVP: Map-Aware Visuomotor Policies for Mobile Manipulation#1043115
Record · ID 1327421
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