OctoMap: an efficient probabilistic 3D mapping framework based on octrees

By Armin Hornung, Kai M. Wurm, Maren Bennewitz, Cyrill Stachniss, Wolfram Burgard. 2013

3,129 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition, 3D Vision & Pose, Robotics & Control

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Citations in the corpus

Hypersim: A Photorealistic Synthetic Dataset for Holistic Indoor Scene Understanding (2020, methodology): “We store our occupancy volume efficiently in an OctoMap data structure [30].”
RGB-D datasets using microsoft kinect or similar sensors: a survey (2016, background): “Six research publications about evaluating ego-motion estimation and SLAM over TUM Benchmark dataset are [21, 38, 45, 84, 86, 87].”
RotorS—A Modular Gazebo MAV Simulator Framework (2016, methodology): “The reader will be provided with representative simulation environments including the widely used octomap representation of the 3D occupancy grid [4].”
3-D Mapping With an RGB-D Camera (2014, methodology): “On the downside, the creation of an OctoMap requires more computational resources since every depth measurement is raycasted into the map.”
DS-SLAM: A Semantic Visual SLAM towards Dynamic Environments (2018, methodology): “DS-SLAM creates a separate thread to build a dense semantic 3D octo-tree map [8].”
Mesh Manifold Based Riemannian Motion Planning for Omnidirectional Micro Aerial Vehicles (2021, background): “Common examples are octrees [11] and hash-based voxel grids [12].”
TartanAir: A Dataset to Push the Limits of Visual SLAM (2020, background): “One such map representation is an occupancy map [27].”
Voxblox: Incremental 3D Euclidean Signed Distance Fields for on-board MAV planning (2016, methodology): “One of the most popular 3D occupancy maps is called Octomap [3], which uses a hierarchical octree structure to store occupancy probabilities.”
Neural Topological SLAM for Visual Navigation (2020, background): “Researchers have used explicit metric spatial representations [12], and have considered how can such representations be built with different sensors [19,26–28,38], and how can agents be localized against such representations [11].”
Place categorization and semantic mapping on a mobile robot (2015, methodology): “Finally, a clamping step similar to that used in Octomap [32] ensures that lmin ≤ Lk(x̂i|z1:t) ≤ lmax.”
A Survey on Active Simultaneous Localization and Mapping: State of the Art and New Frontiers (2022, methodology): “D include OctoMaps [82], Supereight [83], and voxel maps [84], all of which have been also used in active SLAM [85], [86], [87], [88].”
Advanced closed loop visual navigation for micro aerial vehicles (2014, methodology): “The collision checks are performed using OctoMap (Hornung et al., 2013) representing the environment, allowing for efficient storage and fast lookups.”
RTAB‐Map as an open‐source lidar and visual simultaneous localization and mapping library for large‐scale and long‐term online operation (2018, background): “They can also generate a 3D occupancy grid (OctoMap; Hornung et al., 2013) and a dense point cloud for depending modules.”
Planning Dynamically Feasible Trajectories for Quadrotors Using Safe Flight Corridors in 3-D Complex Environments (2017, methodology): “[7] requires an OctoMap [10] representation and produces a sequences of axes-aligned cubes in free space to generate trajectories.”
KITTI-360: A Novel Dataset and Benchmarks for Urban Scene Understanding in 2D and 3D (2021, methodology): “Speciﬁcally, we build a 3D occupancy volumetric grid V for each batch by fusing Velodyne observations using Octomap [44].”
Autonomous aerial navigation using monocular visual‐inertial fusion (2018, methodology): “F IGURE 1 A synthetic and closeup of our aerial robot platform: (1) Perception core; (2) DJI Lightbridge 2; (3) DJI Phantom 4 Pro battery; (4) DJI Takyon Z425-M ESC; (5) DJI E310motors; (6) iPad Pro; (7) radio controller”
Real-Time Perception Meets Reactive Motion Generation (2017, methodology): “, using OctoMaps [27].”