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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2503.13704 |
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| _version_ | 1866908273021550592 |
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| author | Coumar, Sai Chang, Gilbert Kodkani, Nihar Kingston, Zachary |
| author_facet | Coumar, Sai Chang, Gilbert Kodkani, Nihar Kingston, Zachary |
| contents | Many applications in robotics require primitive spherical geometry, especially in cases where efficient distance queries are necessary. Manual creation of spherical models is time-consuming and prone to errors. This paper presents Foam, a tool to generate spherical approximations of robot geometry from an input Universal Robot Description Format (URDF) file. Foam provides a robust preprocessing pipeline to handle mesh defects and a number of configuration parameters to control the level and approximation of the spherization, and generates an output URDF with collision geometry specified only by spheres. We demonstrate Foam on a number of standard robot models on common tasks, and demonstrate improved collision checking and distance query performance with only a minor loss in fidelity compared to the true collision geometry. We release our tool as an open source Python library and containerized command-line application to facilitate adoption across the robotics community. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_13704 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Foam: A Tool for Spherical Approximation of Robot Geometry Coumar, Sai Chang, Gilbert Kodkani, Nihar Kingston, Zachary Robotics Computational Geometry Many applications in robotics require primitive spherical geometry, especially in cases where efficient distance queries are necessary. Manual creation of spherical models is time-consuming and prone to errors. This paper presents Foam, a tool to generate spherical approximations of robot geometry from an input Universal Robot Description Format (URDF) file. Foam provides a robust preprocessing pipeline to handle mesh defects and a number of configuration parameters to control the level and approximation of the spherization, and generates an output URDF with collision geometry specified only by spheres. We demonstrate Foam on a number of standard robot models on common tasks, and demonstrate improved collision checking and distance query performance with only a minor loss in fidelity compared to the true collision geometry. We release our tool as an open source Python library and containerized command-line application to facilitate adoption across the robotics community. |
| title | Foam: A Tool for Spherical Approximation of Robot Geometry |
| topic | Robotics Computational Geometry |
| url | https://arxiv.org/abs/2503.13704 |