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arXiv · 2609.07165

State-of-the-Art in Learning-by-Demonstration with Passive Observation for Industrial Assembly Automation

David Koetter·Oliver Petrovic·Christian Brecher
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Abstract

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 the generalization of the perceived demonstration. We specifically investigate one-shot approaches where only a single demonstration is required. The review evaluates how systems adapt to new assemblies using this limited data. We identify a shift towards object-centric perception, allowing learned primitives to be transferred to new product variants with minimal training.

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David Koetter, Oliver Petrovic, Christian Brecher. 2026-09-07. State-of-the-Art in Learning-by-Demonstration with Passive Observation for Industrial Assembly Automation. https://arxiv.org/abs/2609.07165

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