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| Main Authors: | , , , , |
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| Format: | Recurso digital |
| Language: | English |
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Zenodo
2026
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| Online Access: | https://doi.org/10.5281/zenodo.19612559 |
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| _version_ | 1866902123602509824 |
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| author | De Toni, Alessandro Govoni, Andrea Ida', Edoardo Carricato, Marco Palli, Gianluca |
| author_facet | De Toni, Alessandro Govoni, Andrea Ida', Edoardo Carricato, Marco Palli, Gianluca |
| contents | <p>This package contains the software related to the submitted article: "<em>FastCMap: GPU-Accelerated Parallel Computation of Capability Maps for Serial Robots</em>".<br><br><strong>FastCMap</strong> is a GPU-accelerated software library for computing high-resolution capability maps and workspace analysis of robotic manipulators. It combines vectorized inverse kinematics, manipulability metrics, and collision detection on PyTorch to enable rapid analysis of robot dexterity, reachability, and safety constraints. The framework is modular and extensible, supporting custom metrics, collision methods, and robot kinematics through a dynamic loader system. It provides an integrated PyQt5 GUI for configuration and interactive 3D visualization, making it ideal for robot design optimization, workspace planning, and performance benchmarking.</p> <div class="markdown-heading">More details on installation and usage in the README contained in the attached folder.</div> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_19612559 |
| institution | Zenodo |
| language | eng |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | FastCMap Library De Toni, Alessandro Govoni, Andrea Ida', Edoardo Carricato, Marco Palli, Gianluca <p>This package contains the software related to the submitted article: "<em>FastCMap: GPU-Accelerated Parallel Computation of Capability Maps for Serial Robots</em>".<br><br><strong>FastCMap</strong> is a GPU-accelerated software library for computing high-resolution capability maps and workspace analysis of robotic manipulators. It combines vectorized inverse kinematics, manipulability metrics, and collision detection on PyTorch to enable rapid analysis of robot dexterity, reachability, and safety constraints. The framework is modular and extensible, supporting custom metrics, collision methods, and robot kinematics through a dynamic loader system. It provides an integrated PyQt5 GUI for configuration and interactive 3D visualization, making it ideal for robot design optimization, workspace planning, and performance benchmarking.</p> <div class="markdown-heading">More details on installation and usage in the README contained in the attached folder.</div> |
| title | FastCMap Library |
| url | https://doi.org/10.5281/zenodo.19612559 |