arXiv (All)
open access
State-of-the-Art in Learning-by-Demonstration with Passive Observation for Industrial Assembly Automation
Learning-by-Demonstration (LbD) enables intuitive robot programming by capturing expert skills, which is crucial for agility in high-mix, low- volume manufacturing. This systematic literature review analyzes passive LbD for industrial assembly processes, focusing on the perception architecture and t
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
- ExpertGen: Scalable Sim-to-Real Expert Policy Learning from Imperfect Behavior Priors#1142643
- In-Context Learning for Robots: Methods and Applications#1130854
- In-context Robot Learning Made Simple: A Democratized Recipe for Manipulation Tasks#1142468
- Learning Beyond What Humans Can Demonstrate#1051388
- Demonstration-Free Success-Probability Reward Learning for Generalist Robot Policies#1118726
Record · ID 975221
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