arXiv (All)
open access
StereoPolicy: Improving Robotic Manipulation Policies via Stereo Perception
Recent advances in robot imitation learning have produced powerful visuomotor policies that manipulate diverse objects from visual inputs. However, monocular observations lack depth information, which is critical for precise manipulation in cluttered or geometrically complex scenes. Explicit depth m
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
- StereoPatch: Patch-Aligned RGB-Depth Fusion for Spatial Perception in Robot Manipulation#1109507
- GRAFT: Grounded and Efficient Online Reinforcement Adaptation for Fine-Grained Robot Manipulation#780772
- GRAFT: Grounded and Efficient Online Reinforcement Adaptation for Fine-Grained Robot Manipulation#779397
- MINERVA: How Small Can a Manipulation Policy Be and Still Solve LIBERO?#926606
- Bi-MoDe: Bilateral Control-based Imitation Learning via Modifier-Conditioned Decoding for Modulation of Execution Speed and Contact Intensity#1110433
Record · ID 1117406
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