Self-made Gazebo maps and models for public
- Exploration map used in the paper:
- REAL: Rapid Exploration with Active Loop-Closing toward Large-Scale 3D Mapping using UAVs, 2021 IROS
- QR-SCAN: Traversable Region Scan for Quadruped Robot Exploration using Lightweight Precomputed Trajectory, 2021 ICCAS
- Maze with height map (hills and cliff) environment
- Maze with hole-ground
- Peacock exploration: a lightweight exploration for UAV using control-efficient trajectory, 2020 RiTA
- Maze with 3D obstacles
- (Pending) LiDAR-camera Exploration and Inspection Path Planning, 2023 RA-L
- Map used in the paper:
- ROLAND: Robust Landing of UAV on Moving Platform using Object Detection and UWB based Extended Kalman Filter, 2021 ICCAS
- Wall bounded world (with obstacles)
- ROLAND: Robust Landing of UAV on Moving Platform using Object Detection and UWB based Extended Kalman Filter, 2021 ICCAS
- Textureless and featureless map for visual-inertial odometry used in the paper:
- STEP: State Estimator for Legged Robots Using a Preintegrated Foot Velocity Factor, 2022 IEEE RA-L
- Iced outdoor mountain
- STEP: State Estimator for Legged Robots Using a Preintegrated Foot Velocity Factor, 2022 IEEE RA-L
- War site scenario map used in the paper:
- Quadruped robot competition map
- Drone competition map
- ADD2021 K-DARPA
- KVRC2022 - map, video, competition github
[Click to fold/unfold pictures]
-
Quadruped robot competition map
-
Drone competition map - ADD2021 K-DARPA
-
Drone competition map - KVRC2022
-
Small-scale maze
-
Large-scale mine
-
Maze with height maps
-
Maze with hole-ground
-
Maze with 3D obstacles
-
Vertical tunnel
-
Large-scale and complex environment
-
Tall wall-bounded world
-
Iced outdoor mountain
-
Military fortress
-
Reconstruction models used in the paper:
- CEO-MLCPP: Control-Efficient and Obstacle-aware Multi-Layer Coverage Path Planner for 3D reconstruction with UAVs, 2022 RiTA
- Two-Stage Optimization-Based Energy-Efficient Coverage Path Planner for 3D reconstruction, 2023 KRoC
- THE-Planner: Topological and Hierarchical Exploration Path Planner for Fast and Coarse 3D Mapping of Outdoor Structures with UAVs, 2023 UR
- EQA-CPP: Energy and Quality-Aware Coverage Path Planner for 3D reconstruction with UAVs, 2023 RA-L (pending)
-
Models not used in any paper:
[Click to fold/unfold pictures]
-
Models in
recon1.tar.xz
file (Big-Ben
,Louisiana State House
,Eiffel Tower
,Japanese temple
,Bridge
) -
Models in
recon2.tar.xz
file (Alexander Nevsky Cathedral
,At Tin Mosque
,Japanese temple2
) -
Models in
recon3.tar.xz
file (San Adrian thermal powerplant
,Khram Pokrova
,Orthodox church
) -
Models in
recon4.tar.xz
file (Tomb of Tu Duc
,Stone church
) -
Models in
recon5.tar.xz
file (Mexico City Cathedral
)
$ tar -xf <NAME>.tar.xz
- Clone the git, add the folder in
GAZEBO_MODEL_PATH
- (Necessary) Add
common models
to environment first
$ git clone https://github.com/engcang/gazebo_maps
$ echo "export GAZEBO_MODEL_PATH=$GAZEBO_MODEL_PATH:$(pwd)/gazebo_maps/common_models" >> ~/.bashrc
- (Optional) add the wanted world to environment
$ echo "export GAZEBO_MODEL_PATH=$GAZEBO_MODEL_PATH:$(pwd)/gazebo_maps/height_maze" >> ~/.bashrc
$ echo "export GAZEBO_MODEL_PATH=$GAZEBO_MODEL_PATH:$(pwd)/gazebo_maps/3d_maze" >> ~/.bashrc
$ echo "export GAZEBO_MODEL_PATH=$GAZEBO_MODEL_PATH:$(pwd)/gazebo_maps/large_mine_abandoned" >> ~/.bashrc
...
Add the world/model path you want!!
$ source ~/.bashrc
- launch the
world
$ roslaunch gazebo_ros empty_world.launch world_name:=$(pwd)/gazebo_maps/small_maze/smaze2d.world
or
$ roslaunch gazebo_ros empty_world.launch world_name:=$(pwd)/gazebo_maps/3d_maze/eazy_maze.world
or
...
Launch the world/model you want!