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Ditch robot-specific terrain labels: Trinity learns generalizable terrain understanding from visual appearance alone, unlocking transferability across diverse robotic platforms.
LiDAR odometry can be made significantly more robust in challenging, feature-poor environments by representing surfaces as compact voxel-wise oriented height images and focusing registration on geometrically informative regions.
Achieve faster, near-optimal path planning in complex 3D environments by combining any-angle search with multi-resolution grids, outperforming even sampling-based methods.
