Deep Federated Unrolling for Boosting Low-resolution Lidar-based SLAM Solutions

This demo presents a novel Deep Federated Unrolling (FL-DU) super-resolution (SR) approach for enabling low-resolution Lidar-based Simultaneous Localization and Mapping (SLAM) solutions. The proposed system enhances the accuracy of low-cost Lidar sensors via novel explainable by design neural networks and by enabling collaboration between individual vehicles during learning, thereby minimizing the need for costly high-resolution Lidar sensors, leading to significant cost reductions without affecting the SLAM accuracy. Our demo is available on https://www.youtube.com/watch?v=Fp_nBrD6NiY.