SE(2) NavMesh adds yaw-dependent traversability layers to polygonal navigation meshes, paired with ASA hierarchical pathfinding and incremental point-cloud updates, claiming over 50% more traversable area than standard navmeshes.
Octomap: An efficient probabilistic 3d mapping framework based on octrees
4 Pith papers cite this work. Polarity classification is still indexing.
4
Pith papers citing it
fields
cs.RO 4years
2026 4representative citing papers
STEMbot climbs 7–33 mm stems with geometric PIN-SLAM, semantic OcTree mapping, and manifold-constrained A* planning, achieving sub-centimeter reconstructions and autonomous navigation on four plants.
SOCC-ICP unifies semantic occupancy grid mapping with LiDAR scan alignment via adaptive point-to-point or point-to-plane ICP, achieving competitive odometry performance while producing maps usable for planning.
A surface extraction framework reduces the navigation state space by over 80% while achieving 100% planning success and sub-millisecond A* searches in Matterport3D and PCT scenes.
citing papers explorer
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SE(2) Navigation Mesh
SE(2) NavMesh adds yaw-dependent traversability layers to polygonal navigation meshes, paired with ASA hierarchical pathfinding and incremental point-cloud updates, claiming over 50% more traversable area than standard navmeshes.
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STEMbot: A Compliant Robot for Under-Canopy Plant Navigation
STEMbot climbs 7–33 mm stems with geometric PIN-SLAM, semantic OcTree mapping, and manifold-constrained A* planning, achieving sub-centimeter reconstructions and autonomous navigation on four plants.
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SOCC-ICP: Semantics-Assisted Odometry based on Occupancy Grids and ICP
SOCC-ICP unifies semantic occupancy grid mapping with LiDAR scan alignment via adaptive point-to-point or point-to-plane ICP, achieving competitive odometry performance while producing maps usable for planning.
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Beyond Geometry: Efficient Topologically-Grounded Navigation in Complex 3D Environments
A surface extraction framework reduces the navigation state space by over 80% while achieving 100% planning success and sub-millisecond A* searches in Matterport3D and PCT scenes.