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TravKAN achieves superior traversability analysis by combining fast, interpretable models with novel features from LiDAR reflectivity, revealing critical insights into terrain interactions.
TACO achieves over 90% success in robustly optimizing SLAM trajectories, even in the presence of up to 50% outlier measurements.
Current 3D anomaly detection struggles with real-world complexity, but this new approach directly models inlier feature distributions, achieving state-of-the-art results and offering a more robust solution.
