Abstract
Abstract The objective of this work is to implement a Model Predictive Control (MPC) algorithm on an embedded Graphics Processing Unit (GPU) card. A MPC model for the autonomous navigation of a ground mobile robot is proposed. GPU CUDA code implementation and CUDA optimization techniques are discussed for this specific problem. The GPU-accelerated application permits extending the prediction horizon and evaluating more future trajectories compared to usual time-constrained CPU implementations. Simulation results and a preliminary experiment are presented to demonstrate the efficiency of the real-time algorithm.
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