50% computational speedup for MPPI control with GPU acceleration
Research Engineer
3 months (Mar 2024 - May 2024)
C++, LibTorch, CUDA, MPPI, GPU Acceleration
50% computational speedup for Model Predictive Path Integral (MPPI) control framework through efficient C++ implementation with GPU acceleration.
Offroad autonomous navigation requires real-time trajectory optimization. Traditional implementations too slow for embedded platforms in challenging terrain.
Implemented MPPI control in C++ using LibTorch and CUDA optimization. Validated algorithm robustness through replay data simulations. Integrated GPU-accelerated trajectory sampling for resource-constrained embedded deployment.