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https://github.com/HKUST-Aerial-Robotics/A-LOAM
Advanced implementation of LOAM
https://github.com/HKUST-Aerial-Robotics/A-LOAM
lidar loam slam
Last synced: 7 days ago
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Advanced implementation of LOAM
- Host: GitHub
- URL: https://github.com/HKUST-Aerial-Robotics/A-LOAM
- Owner: HKUST-Aerial-Robotics
- License: other
- Created: 2019-03-06T15:31:46.000Z (over 5 years ago)
- Default Branch: devel
- Last Pushed: 2023-10-19T11:18:59.000Z (about 1 year ago)
- Last Synced: 2024-10-16T01:41:00.377Z (19 days ago)
- Topics: lidar, loam, slam
- Language: C++
- Size: 23.4 MB
- Stars: 2,112
- Watchers: 54
- Forks: 796
- Open Issues: 48
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- Awesome-SLAM - A-LOAM
- awesome-robotic-tooling - A-LOAM - Advanced implementation of LOAM (Localization / SLAM)
- awesome-robotic-tooling - A-LOAM - Advanced implementation of LOAM. (Simultaneous Localization and Mapping / Lidar)
README
# A-LOAM
## Advanced implementation of LOAM
A-LOAM is an Advanced implementation of LOAM (J. Zhang and S. Singh. LOAM: Lidar Odometry and Mapping in Real-time), which uses Eigen and Ceres Solver to simplify code structure. This code is modified from LOAM and [LOAM_NOTED](https://github.com/cuitaixiang/LOAM_NOTED). This code is clean and simple without complicated mathematical derivation and redundant operations. It is a good learning material for SLAM beginners.
**Modifier:** [Tong Qin](http://www.qintonguav.com), [Shaozu Cao](https://github.com/shaozu)
## 1. Prerequisites
### 1.1 **Ubuntu** and **ROS**
Ubuntu 64-bit 16.04 or 18.04.
ROS Kinetic or Melodic. [ROS Installation](http://wiki.ros.org/ROS/Installation)
### 1.2. **Ceres Solver**
Follow [Ceres Installation](http://ceres-solver.org/installation.html).
### 1.3. **PCL**
Follow [PCL Installation](http://www.pointclouds.org/downloads/linux.html).
## 2. Build A-LOAM
Clone the repository and catkin_make:
```
cd ~/catkin_ws/src
git clone https://github.com/HKUST-Aerial-Robotics/A-LOAM.git
cd ../
catkin_make
source ~/catkin_ws/devel/setup.bash
```
## 3. Velodyne VLP-16 Example
Download [NSH indoor outdoor](https://drive.google.com/file/d/1s05tBQOLNEDDurlg48KiUWxCp-YqYyGH/view) to YOUR_DATASET_FOLDER.
```
roslaunch aloam_velodyne aloam_velodyne_VLP_16.launch
rosbag play YOUR_DATASET_FOLDER/nsh_indoor_outdoor.bag
```
## 4. KITTI Example (Velodyne HDL-64)
Download [KITTI Odometry dataset](http://www.cvlibs.net/datasets/kitti/eval_odometry.php) to YOUR_DATASET_FOLDER and set the `dataset_folder` and `sequence_number` parameters in `kitti_helper.launch` file. Note you also convert KITTI dataset to bag file for easy use by setting proper parameters in `kitti_helper.launch`.
```
roslaunch aloam_velodyne aloam_velodyne_HDL_64.launch
roslaunch aloam_velodyne kitti_helper.launch
```
## 5. Docker Support
To further facilitate the building process, we add docker in our code. Docker environment is like a sandbox, thus makes our code environment-independent. To run with docker, first make sure [ros](http://wiki.ros.org/ROS/Installation) and [docker](https://docs.docker.com/install/linux/docker-ce/ubuntu/) are installed on your machine. Then add your account to `docker` group by `sudo usermod -aG docker $YOUR_USER_NAME`. **Relaunch the terminal or logout and re-login if you get `Permission denied` error**, type:
```
cd ~/catkin_ws/src/A-LOAM/docker
make build
```
The build process may take a while depends on your machine. After that, run `./run.sh 16` or `./run.sh 64` to launch A-LOAM, then you should be able to see the result.
## 6.Acknowledgements
Thanks for LOAM(J. Zhang and S. Singh. LOAM: Lidar Odometry and Mapping in Real-time) and [LOAM_NOTED](https://github.com/cuitaixiang/LOAM_NOTED).