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arXiv · 2509.10007

Gaussian path model library for intuitive robot motion programming by demonstration

Samuli Soutukorva·Markku Suomalainen·Martin Kollingbaum·Tapio Heikkilä
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Abstract

This paper presents a system for generating Gaussian path models from teaching data representing the path shape. In addition, methods for using these path models to classify human demonstrations of paths are introduced. By generating a library of multiple Gaussian path models of various shapes, human demonstrations can be used for intuitive robot motion programming. A method for modifying existing Gaussian path models by demonstration through geometric analysis is also presented.

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Samuli Soutukorva, Markku Suomalainen, Martin Kollingbaum, Tapio Heikkilä. 2025-09-12. Gaussian path model library for intuitive robot motion programming by demonstration. https://arxiv.org/abs/2509.10007

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