VIMPPI: Enhancing Model Predictive Path Integral Control with Variational Integration for Underactuated Systems
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arXiv
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| Hauptverfasser: | , , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| _version_ | 1866908362917019648 |
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| author | Alentev, Igor Kozlov, Lev Domrachev, Ivan Nedelchev, Simeon Ryu, Jee-Hwan |
| author_facet | Alentev, Igor Kozlov, Lev Domrachev, Ivan Nedelchev, Simeon Ryu, Jee-Hwan |
| contents | This paper presents VIMPPI, a novel control approach for underactuated double pendulum systems developed for the AI Olympics competition. We enhance the Model Predictive Path Integral framework by incorporating variational integration techniques, enabling longer planning horizons without additional computational cost. Operating at 500-700 Hz with control interpolation and disturbance detection mechanisms, VIMPPI substantially outperforms both baseline methods and alternative MPPI implementations |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2505_05507 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | VIMPPI: Enhancing Model Predictive Path Integral Control with Variational Integration for Underactuated Systems Alentev, Igor Kozlov, Lev Domrachev, Ivan Nedelchev, Simeon Ryu, Jee-Hwan Systems and Control Robotics This paper presents VIMPPI, a novel control approach for underactuated double pendulum systems developed for the AI Olympics competition. We enhance the Model Predictive Path Integral framework by incorporating variational integration techniques, enabling longer planning horizons without additional computational cost. Operating at 500-700 Hz with control interpolation and disturbance detection mechanisms, VIMPPI substantially outperforms both baseline methods and alternative MPPI implementations |
| title | VIMPPI: Enhancing Model Predictive Path Integral Control with Variational Integration for Underactuated Systems |
| topic | Systems and Control Robotics |
| url | https://arxiv.org/abs/2505.05507 |