The Dynamic Model of the UR10 Robot and its ROS2 Integration
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arXiv
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| Auteurs principaux: | , , |
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| Format: | Preprint |
| Publié: |
2025
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| _version_ | 1866912423650263040 |
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| author | Petrone, Vincenzo Ferrentino, Enrico Chiacchio, Pasquale |
| author_facet | Petrone, Vincenzo Ferrentino, Enrico Chiacchio, Pasquale |
| contents | This paper presents the full dynamic model of the UR10 industrial robot. A triple-stage identification approach is adopted to estimate the manipulator's dynamic coefficients. First, linear parameters are computed using a standard linear regression algorithm. Subsequently, nonlinear friction parameters are estimated according to a sigmoidal model. Lastly, motor drive gains are devised to map estimated joint currents to torques. The overall identified model can be used for both control and planning purposes, as the accompanied ROS2 software can be easily reconfigured to account for a generic payload. The estimated robot model is experimentally validated against a set of exciting trajectories and compared to the state-of-the-art model for the same manipulator, achieving higher current prediction accuracy (up to a factor of 4.43) and more precise motor gains. The related software is available at https://codeocean.com/capsule/8515919/tree/v2. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2502_11940 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | The Dynamic Model of the UR10 Robot and its ROS2 Integration Petrone, Vincenzo Ferrentino, Enrico Chiacchio, Pasquale Robotics This paper presents the full dynamic model of the UR10 industrial robot. A triple-stage identification approach is adopted to estimate the manipulator's dynamic coefficients. First, linear parameters are computed using a standard linear regression algorithm. Subsequently, nonlinear friction parameters are estimated according to a sigmoidal model. Lastly, motor drive gains are devised to map estimated joint currents to torques. The overall identified model can be used for both control and planning purposes, as the accompanied ROS2 software can be easily reconfigured to account for a generic payload. The estimated robot model is experimentally validated against a set of exciting trajectories and compared to the state-of-the-art model for the same manipulator, achieving higher current prediction accuracy (up to a factor of 4.43) and more precise motor gains. The related software is available at https://codeocean.com/capsule/8515919/tree/v2. |
| title | The Dynamic Model of the UR10 Robot and its ROS2 Integration |
| topic | Robotics |
| url | https://arxiv.org/abs/2502.11940 |