VIMPPI: Enhancing Model Predictive Path Integral Control with Variational Integration for Underactuated Systems

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

@article{alentev2025_2505.05507,
  title={ VIMPPI: Enhancing Model Predictive Path Integral Control with Variational Integration for Underactuated Systems },
  author={ Igor Alentev and Lev Kozlov and Ivan Domrachev and Simeon Nedelchev and Jee-Hwan Ryu },
  journal={arXiv preprint arXiv:2505.05507},
  year={ 2025 }
}