ACDSLab/MPPI-Generic
Templated C++/CUDA implementation of Model Predictive Path Integral Control (MPPI)
What it solves
MPPI-Generic provides a high-performance implementation of Model Predictive Path Integral (MPPI) control, allowing for stochastic trajectory optimization in robotic systems.
How it works
It is a C++/CUDA header-only library that leverages NVIDIA GPUs to parallelize the computation of multiple potential trajectories, enabling the system to find an optimal path based on a cost function.
Who it’s for
Researchers and engineers working on robotics, control theory, and trajectory optimization who need a GPU-accelerated implementation of the MPPI algorithm.
Highlights
- Header-only C++/CUDA library for easy integration.
- Compatible with CUDA 10 and newer (CUDA 11.7+ recommended).
- Built on the Eigen library for linear algebra operations.
- Supports unit testing for verification.
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