DUFOMap is a novel dynamic awareness mapping framework designed for efficient online processing. It aims to address the challenge of detecting and removing dynamic objects from point cloud data, which is crucial for tasks like localization and planning in robotics. The method operates on point clouds discretized into voxels, using ray casting to identify fully observed empty regions (voids). Points inside these voids are classified as dynamic. DUFOMap accounts for sensor noise and localization errors, making it suitable for real-time applications. Extensive experiments across various datasets and sensors demonstrate that DUFOMap outperforms state-of-the-art methods in terms of accuracy and computational efficiency. The method is open-source and can be used for both offline map cleaning and online dynamic point detection.DUFOMap is a novel dynamic awareness mapping framework designed for efficient online processing. It aims to address the challenge of detecting and removing dynamic objects from point cloud data, which is crucial for tasks like localization and planning in robotics. The method operates on point clouds discretized into voxels, using ray casting to identify fully observed empty regions (voids). Points inside these voids are classified as dynamic. DUFOMap accounts for sensor noise and localization errors, making it suitable for real-time applications. Extensive experiments across various datasets and sensors demonstrate that DUFOMap outperforms state-of-the-art methods in terms of accuracy and computational efficiency. The method is open-source and can be used for both offline map cleaning and online dynamic point detection.