Gaussian path model library for intuitive robot motion programming by demonstration
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | |
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| _version_ | 1866915494699728896 |
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| author | Soutukorva, Samuli Suomalainen, Markku Kollingbaum, Martin Heikkilä, Tapio |
| author_facet | Soutukorva, Samuli Suomalainen, Markku Kollingbaum, Martin Heikkilä, Tapio |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_10007 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Gaussian path model library for intuitive robot motion programming by demonstration Soutukorva, Samuli Suomalainen, Markku Kollingbaum, Martin Heikkilä, Tapio Robotics 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. |
| title | Gaussian path model library for intuitive robot motion programming by demonstration |
| topic | Robotics |
| url | https://arxiv.org/abs/2509.10007 |